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Nonequilibrium Thermodynamics of Cell Signaling Journal of Thermodynamics Volume 2012 (2012), Article ID 432143, 10 pages Research Article Nonequilibrium Thermodynamics of Cell Signaling Computational Genomics Department, National Institute of Genomic Medicine, Periférico Sur 4809, Col. Arenal Tepepan, Delegación Tlalpan, 14610 Mexico City, DF, Mexico Received 12 March 2012; Revised 7 June 2012; Accepted 9 June 2012 Academic Editor: Ali-Akbar Saboury Copyright © 2012 Enrique Hernández-Lemus. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Signal transduction inside and across the cells, also called cellular signaling, is key to most biological functions and is ultimately related with both life and death of the organisms. The processes giving rise to the propagation of biosignals are complex and extremely cooperative and occur in a far-from thermodynamic equilibrium regime. They are also driven by activation kinetics strongly dependent on local energetics. For these reasons, a nonequilibrium thermodynamical description, taking into account not just the activation of second messengers, but also transport processes and dissipation is desirable. Here we present a proposal for such a formalism, that considers cells as small thermodynamical systems and incorporates the role of fluctuations as intrinsic to the dynamics in a spirit guided by mesoscopic nonequilibrium thermodynamics. We present also a minimal model for cellular signaling that includes contributions from activation, transport, and intrinsic fluctuations. We finally illustrate its feasibility by considering the case of FAS signaling which is a vital signal transduction pathway that determines either cell survival or death by apoptosis. 1. Introduction Survival of living organisms is intimately linked to their ability to react quite efficiently to even extremely weak external signals. Common examples are the reaction of the human eye to single light photons [1, 2], the reaction of a male butterfly to a single pheromone molecule coming from a female at a distance that sometimes is in the order of kilometers [3], and so forth. Cellular receptors react to hormones, cytokines, or antigens at very low concentrations. This strong reaction to a weak impulse is attained by an amplification process which is performed by means of special pathways of free energy transduction. Mechanisms such as immune system response, thermal-shock inhibitions, and cardiovascular rearrangement in response to environmental changes are all mediated by signaling processes. Signal transduction (information flow) is, thus, equally important, if not more important, for the functioning of a living organisms than metabolism and energy flow. Signal transduction or cell signaling is the generic name of the set of concatenated processes or stages in which a cell transforms a certain signal or stimulus—either intercellular or intracellular—into another signal or a specific response. Cell signaling affects the complex arrangement of biochemical reactions inside the cell that takes place by means of enzymes that are bounded to other molecules called second messengers. Each process takes place in fast times, with dynamic ranges between a few milliseconds in most cases, to a few seconds in the case of more complex signaling cascades. Intricate and very sensible molecular biology experiments have shown cell signaling to be rate processes, that is, kinetic-guided phenomena determined by previous systems settings The wide variety of physicochemical signals to which cells may respond may seem to imply on a wide range of signal transduction mechanisms. However, only a handful of event chains is able to generate proper response to every stimulus in different cell subtypes which points to generalistic strategies commonly beginning with the action of cell receptors. Many signal transduction processes are then usually started by the adhesion of a ligand protein to a membrane receptor that then activates either itself or other receptor (or series of receptors) thus converting the initial stimulus into a response that once inside the cell provokes a chain of biochemical events known as a signaling cascade or second messenger pathway which results in the amplification of the signal. The archetypal example here is that of the epinephrine cascade. It is known that epinephrine (adrenaline) stimulates the liver to convert glycogen to glucose in liver cells, but epinephrine alone would not convert glycogen to glucose. In an outstanding experimental tour de force that granted him the 1971 Nobel Prize in Physiology or Medicine, Earl Sutherland found that epinephrine had to trigger a second messenger, cyclic AMP, for the liver to convert glycogen to glucose [5]. Secondary messenger systems can be synthesized and activated by the action of enzymes, for instance, cyclases that synthesize cyclic nucleotides. Second messengers also form by opening of ion channels to allow influx of metal ions (e.g., calcium signaling). These second messengers then bind and activate protein kinases, ion channels, and other proteins continuing the signaling cascade. The role that activation kinetics and other energy-driven dynamic processes play in cell signaling makes evident the need for a thermodynamic description. Most studies to date are based in equilibrium thermodynamics assumptions [6, 7] or, in any case, coarse-grained approaches [8]. Specific applications of nonequilibrium thermodynamics have been studied in the past [9–13] focusing on single features such as switching, sensitivity, and controllability. Thus, a nonequilibrium thermodynamics analysis of cell signaling, describing transport processes, activation kinetics and nonlocal effects is desirable. Some particular cases of signaling dynamics have been studied, even at the nonequilibrium statistical physics level of description, for instance, by means of information theoretical approaches [14]. In such studies, a positive correlation between the channel capacity (i.e., the information-carrying capacity of the signaling networks) and free-energy expenditure has been observed. For phosphorylation-dephosphorylation switches, hydrolysis-free energy is in the sustained high concentration of ATP and low concentrations of ADP, that is, away from thermochemical equilibrium. This deviation from equilibrium implies, among other things, that useful hydrolysis-free energy does not come from the phosphate bond of the ATP molecule alone but from more complex-systemic mechanisms. Nonequilibrium thermodynamic entropy and entropy production have been studied, to gain dynamic signaling information transfer, in insulin transduction [11]. In that case, entropy production rates show a broad secondary peak in time that represents a possible evidence of the decrease of the concentration of membrane GLUT4 (a so called backflow), thus to the reduction of insulin efficiency. Interestingly, at least in that case entropic contributions take a leading role in controlling signaling efficiency. Pathway selectivity driven by receptor-receptor interaction has also been studied by means of thermodynamic models [8]. Ligand-induced oligomerization of cell-surface receptors is driven by cooperative behavior. Oligomerization occurs due to interaction between nearest-neighbor receptors. This type of cooperativity can exhibit a first-order phase transition, corresponding to a jump in the surface density of ligand-receptor complexes. Clustering could be described by the statistical mechanics of a simple lattice Hamiltonian. Receptor-receptor interaction may lead to a first-order phase transition with a discontinuous jump in the receptor density as a function of the receptor chemical potential and/or the ligand concentration [8]. Thermodynamical studies of biomolecular switches could be quantitatively described by a simple 3-state population-shift model, in which the equilibrium between a nonbinding, nonsignaling state and the binding-competent, signaling state is shifted toward the latter upon target binding. Performance of biomolecular switches can be sensibly tuned via mutations that alter their switching thermodynamics [7]. Thermodynamic conditions in the intracellular medium hence alter sensitivity, control, and effective information transfer in signaling networks [14]. Moreover, as we may see later, typical settings in signal transduction correspond with complex nonequilibrium stages [15]. In fact, even relatively simple signaling models such as the phosphorylation-dephosphorylation switches exhibit bistability due to feedback, and the related nonequilibrium steady state even presents a phase transition [16]. Such complex behavior led some researchers to propose that non-linear deterministic biochemical behavior is dynamically trapped between stochastic dynamics, both at the molecular signaling level and at the cellular evolution level [16]. This proposition raised from an analysis of the so-called chemical master equation which is founded in the tenets of non-linear nonequilibrium thermodynamics [10, 17]. Thermodynamic models of cell signaling aim to model and describe these phenomena at the basic level, and applications of thermodynamic modeling in search of therapeutic action have been recently developed [18]. Claims have been made that fast binding kinetics was advantageous for most targets with a couple of exceptions, that targeting some protein kinases could enhance rather than attenuate the pathway, and that therapeutic doses could be sensitive to the kinetic parameters of drug binding. Thermo-kinetic rates have been shown to play an important role in the dynamics of signaling and immune response. Plasmon resonance-based thermodynamics points out to slow-signaling modified second-messenger variants have similar affinities but distinctly faster dissociation rates that compared with the original messengers and that this may be behind their lower activity. Signaling deregulation could be starting not at the biochemical (recognition) but at the thermodynamical (dissociation rates) levels [19]. In fact, thermodynamic studies are now part of the drug-design tools of pharmaceutical chemistry. In fact, thermodynamic and kinetic analyses are sources of deeper insight into specificity of molecular recognition processes and signaling [20]. Such advances had led to research efforts combining statistical thermodynamic models in combination with experimental data [21]. Preliminary results of these studies are very promising. A proposal for a nonequilibrium thermodynamics formalism including the role of fluctuations as intrinsic to the dynamics, and the role of transport processes is made in this work. We detail a minimal model for cellular signaling that considers activation, transport, and intrinsic fluctuations. The rest of the paper is organized as follows: in Section 2 we discuss the role that stochastic fluctuations and transport processes play in biological signal transduction, in Section 3 we develop a nonequilibrium thermodynamics formalism of cell signaling and from it we derive a minimalist model, Section 4 deals with the biology of direct FAS signaling in apoptosis that in its simplest version (here presented) is akin to our minimalist model, finally in Section 5 we discuss some potential applications, the scope and limitations of our formalism as well as some perspectives. 2. Cell Signaling and Stochasticity and Nonlocality One source of complexity in the nonequilibrium thermodynamical characterization of cell signaling is the fact that a cell is a small system; that is, cellular dimensions do not permit the immediate application of the thermodynamic limit. Specifically, the role that fluctuations and stochasticity may play within such scenarios is not completely clear. A formalism to study small systems thermodynamics in equilibrium has been developed [22, 23], and some results were even expected to extend to local equilibrium settings within cellular sized biosystems [24]. However, one important drawback in completing such theoretical frameworks at that time was the lack of proper experimental settings to test their hypotheses. Nevertheless, with the development of modern techniques, such as microscopic manipulation by means of atomic force microscopes, optical tweezers, and cold traps, this situation has been overcome at least partially. Theories have been developed including mesoscopic thermodynamical approaches [25–29] and also studies made by means of fluctuation theorems [30–33]. Some of these theoretical results have been even experimentally tested. Due to the low copy number of many reactants in cells, and the nonequilibrium nature of the many intracellular reactions, signal transduction may result from stochastic intracellular events. Distribution analyses of cell responses provide a means to probe the stochastic character of intracellular signaling. A goal is to determine the class of stochasticity that affects intracellular pathways [34]. Stochasticity has been measured experimentally, it has been also incorporated in molecular simulations, and it has been discovered that locality and Gaussian behavior are not always present. In fact, transient multipeak distributions have been observed in computer simulations of cell-signaling dynamics. The emergence of these complex distributions cannot be explained using either deterministic chemical kinetics or simple Gaussian noise approximation [35]. Multipeak distributions are typically transient and eventually evolve into single-peak distributions in certain cases these distributions may be stable in the limit of long times. It has also been shown that introducing positive feedback loops results in diminution of the probability distribution complexity. This effect is so strong that even stochastic resonance has been reported in signaling cascades [36] where certain optimal reaction rates minimize the average threshold-crossing time. A noisy signal reaches the threshold more easily when the upstream and downstream reaction time scales are related in a specific way, indicating the existence of internal resonances embedded in cellular signaling cascades [36]; that is, nonequilibrium thermodynamic couplings exist between different modes (as characterized by their corresponding relaxation times) a feature that can be accounted by certain nonequilibrium thermodynamics formalisms (see next section). This may seem to point out on how the rates of various nodes could be collectively tuned in protein-signaling networks in such a way that signals are optimally picked up and biological information is transmitted through the signaling cascade. 3. Irreversible Thermodynamics of Cell Signaling As we have just pointed out, systems outside the thermodynamic limit are characterized by large fluctuations and hence stochastic effects. The classic thermodynamic theory of irreversible process (also called linear irreversible thermodynamics, LIT) [37] provides us with a coarse-grained description of the systems, thus ignoring the molecular nature of matter studying it as a continuum media by means of a phenomenological field theory. As such LIT is not suitable for the description of small systems because it ignores fluctuations that could become the dominant factor in the system's response. Nevertheless, in many instances, it would be desirable to have a thermodynamic theoretical framework to study small systems, most noticeably in cellular and subcellular processes like signal transduction. One way to do so is by considering the stochastic nature of the time evolution of small nonequilibrium systems. This is the approach of Mesoscopic Nonequilibrium Thermodynamics (MNETs) [26]. MNET for small systems can be understood as the extension of the equilibrium thermodynamics of small systems developed by Hill and Chamberlin [22] and Hill [23, 24]. MNET, for instance, was developed to analyze nonequilibrium small systems. Any reduction of the spatio-temporal scale description of a system implies an increase in the number of noncoarse-grained degrees of freedom. These degrees of freedom could be related with the extended variables in extended irreversible thermodynamics (EITs) [38]. In order to characterize such variables, let us say that there exist a set of such non-equilibrated degrees of freedom. is the probability that the system is at a state given by at time . If one assumes [27] that the evolution of the degrees of freedom could be described as a diffusion process in -space, then the corresponding Gibbs equation could be written as is a generalized chemical potential related to the probability density, whose time-dependent expression could be explicitly be written as or in terms of a nonequilibrium work term as follows: The time-evolution of the system could be described as a generalized diffusion process over a potential landscape in the space of mesoscopic variables . This process is driven by a generalized mesoscopic-thermodynamic force whose explicit stochastic origin could be tracked back by means of a Fokker-Planck-like analysis [26, 27]. MNET seems to be a good candidate theory for describing nonequilibrium thermodynamics for small systems, provided that one has a suitable model or microscopic means to infer the probability distribution . MNET and similar approaches are appropriate to deal with activated processes, like a system crossing a potential barrier. Biochemical reactions like the ones involved in signal transduction are clearly in this case. According to [27] the diffusion current in this space could be written in terms of a local fugacity defined as and the expression for the associated flux it will be is an Onsager-like coefficient. After defining a diffusion coefficient and the associated affinity , the integrated rate is given as with . MNET then gives rise to nonlinear kinetic laws like (6). MNET has been applied successfully to biomolecular processes at the cellular level or description [28]. Non-linear kinetics are used to express, for example, RNA unfolding rates as diffusion currents, modeled via transition state theory, giving rise to Arrhenius-type non-linear equations. In that case the current was proportional to the chemical potential difference, so the entropy production was quadratic in that chemical potential gradient. Signal transduction consists of a series of biochemical reactions, and many of these have unexplored chemical kinetics, due to this fact a detailed MNET analysis such as the one described above is unattainable at the present moment. On what follows, we will explore a phenomenologically based approach that takes into account similar considerations as the MNET framework already sketched but does so in a more informal, modeling-like manner. This phenomenological approach is based on the EIT assumption of enlargement of the thermodynamical variables space [39, 40]. Assuming that a generalized entropy-like function exists, we can write down a Gibbs equation which may be written in the following form [38, 41]: or as a differential form Quantities are defined as usual, is the internal energy per mol, T the absolute temperature, p the pressure, the molar volume, is the chemical potential for the species, its concentration (mole fraction), the molar chemical affinity for the reaction producing species, (i.e., being the stoichiometric coefficient for the th species in the th reaction and the corresponding chemical potential), the reaction coordinate for the production of species, , , and are extended fluxes and forces for diverse processes, and is the appropriate scalar product. Here we are considering the presence of thermal processes, but also the energetics of three different contributions due to signal transduction: the effect of bulk chemical potentials related to concentration changes of the signaling molecules in the cellular environment (identified with the subscript ), activation kinetics (considered as generalized chemical reactions) related to the chemical affinities between ligand proteins, membrane receptors and effector proteins in the signaling cascade (identified with the subscript ), and generalized transport processes (including the effects of nonlocal dynamics and delays) considered as extended variables or generalized fluxes and forces (identified with the the subscript ). 3.1. Activation Kinetics We will introduce a simple—although general—model for signal transduction including the action of ligand proteins (LPs), membrane receptors (MRs), effector proteins (EPs), and finally response proteins (RPs). In this idealized model, LPs and MRs play the role of pulls and triggers, then a series of EP steps (not necessarily, but possibly sequential) constitute the core of the signaling cascade and finally, and the RPs when activated constitute the cell’s response to the initial stimulus. The pseudo-chemical reactions could be written as follows: Here the superscript refers to the activated form of the molecule, that is, the form which presents the corresponding biological signaling activity. For a pictorial representation, please refer to Figure 1. 3.2. Generalized Transport Processes Let us recall (8). If we write down explicit expression for second and third terms in the r.h.s. of (8) in the context of signal transduction, we have the following generalized Gibbs form: Since signal transduction occurs within the cell, it is possible to relate an internal work term with the regulation process itself, being this a far-from equilibrium contribution. This nonlocal contribution is given by the generalized force-flux term (last term in the r.h.s. of (14)). This is so as cell signaling often does not occur in situ and also since is the only way to take into account (albeit indirectly) the changes in the local chemical potentials that cause the long tails in the fluctuations distributions characteristic of nonequilibrium small systems (e.g., cells). The term relating second messenger flows due to transduction could be written as a product of extended fluxes and forces . Here refers to the different second messenger species involved. 3.3. A Minimalist Model of Signal Transduction In order to present a full detail of the different energetic contributions in (14), let us consider a minimalist model consisting of just four molecules under isothermal conditions: one triggering ligand protein (LP), one membrane receptor (MR), one effector protein (EP), and one response protein (RP). In such case we have the following 3 pseudoreactions: That will give rise to the following form of (14): Equation (18) considers the energies of formation for four molecules (as given by the ’s), the energies of activation of three species (as given by the chemical affinities ’s) as well as the energies related with transport of the active species, given by their respective thermodynamic forces (’s). If we now refer to (6) for the definition of signaling fluxes [25, 28], we can write down expressions for the ’s, namely, Hence their temporal derivatives are given by: If we consider, as it is often done in irreversible thermodynamics, that the thermodynamic forces ’s are proportional to the fluxes ’s, with proportionality constant , we have We now define the following generalized transport coefficients: By substitution of (22) to (28) in (18) we have Equation (29) gives a complete irreversible thermodynamical description of the minimal model given by (15) to (17). The model is then to be supplemented with the appropriate constitutive relations; in this case, the time evolution for the concentrations, chemical potentials, and chemical affinities as given by biochemical kinetics. The free-energy coupling given by the corresponding generalized Maxwell relations (since is an exact differential form, integrability conditions imply the existence of Maxwell-like relations [41]), as well as Gibbs-Duhem constrains (not all the concentrations and chemical potentials are independent) once explicit kinetics are given, constitutes the energetic core behind the complex processes of signal transduction. This is possibly the key contribution of this work, the explicit derivation from a nonequilibrium thermodynamics formalism showing that cell signaling control is, indeed, an energy-driven process. Of course, free-energy transduction has been known to be responsible for the initiation of signaling cascades. However, our model has shown that every step of the process is controlled and locked via the local chemical potentials even in the presence of stochasticity and fluctuations, provided that the assumptions of MNET hold. 4. Case Study: FAS Signaling in Apoptosis An important family of signal transduction pathways is related with the onset and regulation of programmed cellular death or, apoptosis. Any functional disruption in the balance that apoptotic cells encounter may affect death signaling thus leading to diseases ranging from cancer in the case of subnormal apoptosis to degenerative disorders in supernormal apoptosis. Hence the control of the process as given by signal transduction pathways is of foremost relevance. One of the simplest example of such pathways is apoptosis regulation by FAS signaling. FAS is a cell-surface receptor protein that when triggered by an stimulus induces apoptosis in FAS-expressing cells. This process is highly linked with immune response, as the ligand for FAS, FAS-L, is mostly present on cytotoxic T cells and TH1 cells central players in innate immunity. FAS is composed of an extracellular region, one transmembrane domain, and an intracellular region. FAS activity is governed by interaction with its ligand (FAS-L). Activation of FAS through binding to its ligand or FAS antibody induces apoptosis, which has been confirmed by many experiments [42]. In order for signal transduction to occur, cross-linking of FAS with its ligand must occur. FAS trimerizes to properly bind to its ligand, which exists as a trimer. This creates a clustering of FAS that is necessary for signaling. In its intracellular region, FAS contains a conserved sequence deemed as death domain. An adaptor protein, FADD, interacts with the death domain on the FAS receptor. Subsequent binding to another region of FADD by procaspase 8 promotes grouping of pro-caspase 8 molecules bound to each of the clustered FADD proteins. This entire cluster is sometimes called a death-inducing signaling complex, or DISC [43]. Pro-caspase 8 transactivates itself once grouped, cleaving and releasing active caspase 8 molecules intracellularly. As is clear from Figure 2, there is a correspondence between the model given by (15) to (17) and direct FAS signaling (Figure 2). In this case the ligand protein (LP) is the FAS-L molecule, the membrane receptor (MR) is FAS-R that when activated () becomes FAS and then interacts with the effector protein (EP), in this case FADD, that carries the biosignal activating procaspase-8 (a response protein) that when activated () becomes caspase-8, the molecule responsible for the no-return apoptotic response leading to cellular death. FAS signaling is a well-characterized process [45], some thermodynamic parameters may be thus obtained by experiments [46, 47] or by means of molecular simulations [48]. This is the case of activation energies—especially when activation occurs by means of ATP produced by oxidative phosphorylation—and free energies of formation. However, transport processes have not been measured accurately (and in most cases have not been even measured at all). Being signaling pathways so important for the understanding of cell function, and in many instances for their biomedical importance as pharmacological targets; we hope that this situation soon will change. At the present moment, some insight on particular signaling pathways may be obtained by molecular dynamics simulations [49–54 Experimental techniques have been refined that allow thermomolecular characterization of signaling processes. The technical challenges are, however, gigantic. Cell-signaling thermodynamic parameters must be experimentally measured by combining many different methodologies involving different scales of description: protein-protein electrostatic interactions, the electrohydrodynamic effect of the medium, cleavage and protein structure, free energies of folding/unfolding, transport processes, and so forth. Nonetheless, progress is being made in the actual realization of such experimental challenges, by using a clever combination of surface plasmon resonance (SPR), isothermal titration calorimetry (ITC), and ultracentrifugation (UC) of the thermodynamics of T-cell signaling in the MHC pathway have been unveiled [55]. SPR is extensively used to study receptor/ligand binding both qualitatively and quantitatively. However, results are commonly ambiguous, and every conclusion needs to be independently verified. SPR provides both kinetic and equilibrium data; data acquisition is fast, comparative studies are easily performed, and low affinities can be detected with relatively low amounts of protein. The accuracy of the SPR-derived kinetic constants depends crucially on other various parameters such as mass transport, sensor chip capacity, and flow rate. In conclusion, SPR experiments are useful but partial and sometimes even dubious. In contrast, equilibrium methods, such as ITC, often result in more reliable, specially when used in conjunction with SPR and analytical techniques as ultracentrifugation in which sedimentation velocity, and equilibrium experiments provide insight into the hydrodynamic and thermodynamic properties of the sample, thus enabling the inference of transport parameters and free energies via association constants; on the other hand, SPR experiments could shed some light on biochemical kinetics and their associated relaxation times [55]. ITC has also used in the experimental analysis of the interaction between TRAF and tumor necrosis factor receptors [56]. FAS signaling proceeds by typical physicochemical mechanisms. Being this the case, common ranges for the parameters in cell signaling may be used as proxy values instead. For instance, the characteristic concentration of signaling protein molecules ranges from 0.01 to 1-molar, with molecule counts between 120,000 and 20,000,000 depending on molecular weights and type of cell [57]. RAS concentration in HeLa cells has been measured to be 0.4-molar [58]. Thresholding signal duration times for whole processes range between 2 minutes and 24 hours. NF-B signaling (which is related with FAS signaling) takes about 320 minutes in epithelial cells [59, 60]. In order to figure out the order of magnitude of kinetic parameters, let us consider the case of the values of fluxes and dissociation constants in the Wnt-signaling pathway [61]. Dissociation constants for several second messenger molecules range around 10–1200nM, with protein concentrations in the 15 to 100nM regime. The degradation flux of -catenin via the proteasome is 25nM/h. The characteristic time of the associated phosphorylation-dephosphorylation switch is 2.5 minutes for APC. Relaxation times for GSk3- association/dissociation is 1 minute, and that of Axin degradation is 6 minutes [61]. Decay rates (half-life times) , for signaling molecules in the MAPK pathway and the STAT pathway, are valued between 0.75 and 24h [57]. More closely related with FAS signaling, duration times on switch of apoptosis and duration of apoptotic death in HeLa cells exposed to different levels of TRAIL are between 19 and 27 minutes for switching and between 140 and 660 minutes for cell death [62]. Rate constants for diffusion-limited enzymes may vary around and [63] although there are other kinetic mechanisms for second messengers that in some cases seem to be cell-type specific [64], these figures may serve as reference to infer chemical kinetic behavior since the general behavior seems to be quite common [65]. Once the rate constants are measured, one can infer activation energies from them, following a kinetic model [66]. In relation to energetics, it is known that ATP hydrolysis releases between 28 and 33.5kJ/mol [67] depending on cell type and condition whereas for other energy-rich compounds involved in substrate level phosphorylation range around 23.44 and 88kJ/mol [68]. Free energy profiles may also help us to understand the role that protein-coupling plays in cell signaling. In Ras signaling, for instance, binding free energy determines the fate of Ras/Raf dynamics [69]. Diffusion coefficients measured inside the cell differ according to cell medium and molecule size. Inside the cell nucleus typical diffusion constants vary between 10 and 100 [70]. In reference with signaling proteins, this is usually also the case even in cytoplasm and/or aqueous solution. The diffusion rate of phosphoglycerate kinase (around 45kDa) has been measured as 63.8 [71], while heavier molecules as 62kDa Dextran move slowly, around 39 [72]. Smaller second messenger molecules like insulin (5.808kDa) can diffuse much faster, [73]. The combination of different experimental/computational modeling techniques and estimated parameters just sketched may allow to construct quantitative thermodynamic models for cell signaling, following the lines of the present work, in the near future. 5. Discussion Signaling transduction is a quite complex yet extremely important physicochemical phenomenon in cell biology. As we have seen cellular signaling is characterized by a combination of stochastic effects, activation biochemical kinetics, and multiple transport processes all setup in a far-from thermodynamic equilibrium setting. Is is known that free-energy transduction plays a key role in the process of signaling cascades. For this reason a nonequilibrium thermodynamics description at the mesoscopic level is desirable. In the present work we have presented such a formalism in the context of MNET [26]. The role of stochasticity is taken into account (albeit in an indirect way) by means of incorporating the probability distribution for the nonequilibrated degrees of freedom into a generalized chemical potential as is described in (2) to (6). In this scheme, the thermodynamic forces (equations (25) to (27))—that reflect in a coarse grained way the effect of stochasticity—are identified as the gradients in the space of mesoscopic variables of the logarithm of the ratio of the probability density to its equilibrium value. The main idea is to generalize the definition of the chemical potential to account for these additional mesoscopic variables. Thus it is possible to assume that the evolution of these degrees of freedom is described by a diffusion process and formulate the corresponding Gibbs equation. The effect of generalized transport processes related with the distribution of relaxation times of the kinetics (it takes some (in general different) time for every biochemical reaction to activate the corresponding signaling molecule) and nonlocalities in the molecular processes (i.e., a second messenger has to travel some distance, say by diffusion, until it reaches its target molecule) is given by the last term at the r.h.s. of (14). In particular, relaxation times for the coarse-grained processes are given in terms of generalized transport coefficients (28). Our formalism is written in such a way that we can distinguish between local equilibrium effects (corresponding to the energetics of non-activated molecules at the top of the signaling cascade, as given by the first 4 terms at the r.h.s. of (29)), deterministic activation kinetics depending exclusively on the rate equations for the chemical reactions (corresponding to the 5th to 7th terms at the r.h.s. of (29)), and far-from equilibrium effects, involving both stochasticity and transport processes (terms 8th–13th at the r.h.s. of (29)) involving the dynamics of the evolution of nonconserved variables. We could think of this structure as a hierarchy in which trains of signals are coupled with each other via their relative relaxation times (as given by the corresponding generalized transport coefficients, ( The potential application of such a formalism is wide, in particular with respect to the detailed study of the dynamics for important biological pathways. Consider, for instance, the extremely important scenario of calcium signaling. Phenomena like calcium waves [74, 75] and calcium-induced calcium release [76] could be understood more clearly (and even modeled and simulated) in the light of a nonequilibrium thermodynamic description like the one presented above. For instance, the role of energy releasing pathways in the dynamics and control of cell signaling under a system biology-like philosophy becomes almost crystal clear. In turn these free-energy triggers may be appropriate candidates for pharmacological targets for drug-therapy in cases of diseases associated with abnormal signaling. This may be the case of cardiac arrhythmias, neurological disorders [75, 77], and metabolic diseases [76]. Of course, such general modeling strategy has some drawbacks. 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How to Recognize Recursive Arithmetic Sequences A recursive sequence is an arithmetic sequence in which each term depends on the term(s) before it; the Fibonacci sequence is a well-known example. When your pre-calculus teacher asks you to find any term in a recursive sequence, you use the given term (at least one term, usually the first, is given) and the given formula that allows you to find the other terms in the sequence. You can recognize recursive sequences because the given formula typically has a[n] (the nth term of the sequence) as well as a[n][ – 1] (the term before the nth term of the sequence). In these sequences, you're given a formula (a different one for each sequence), and the directions ask you to find the terms of the sequence. For example, the most famous recursive sequence is the Fibonacci sequence, in which each term after the second term is defined as the sum of the two terms before it. The first term of this sequence is 1, and the second term is 1 also. The formula for the Fibonacci sequence is So if you were asked to find the next three terms of the sequence, you'd have to use the formula as follows: a[3] = a[3 – 2] + a[3 – 1] = a[1] + a[2] = 1 + 1 = 2 a[4] = a[4 – 2] + a[4 – 1][ ]= a[2] + a[3] = 1 + 2 = 3 a[5] = a[5 – 2] + a[5 – 1] = a[3] + a[4] = 2 + 3 = 5 The first ten terms of this sequence are 1, 1, 2, 3, 5, 8, 13, 21, 34, 55. It is very famous because many things in the natural world follow the pattern of the Fibonacci sequence. For examples, the florets in the head of a sunflower form two oppositely directed spirals, 55 of them clockwise and 34 counterclockwise; lilies and irises both have 3 petals; buttercups have 5 petals; and corn marigolds have 13 petals. Seeds of coneflowers and sunflowers have also been observed to follow the same pattern as the Fibonacci sequence. Pine cones and cauliflower also follow this pattern.
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Got Homework? Connect with other students for help. It's a free community. • across MIT Grad Student Online now • laura* Helped 1,000 students Online now • Hero College Math Guru Online now Here's the question you clicked on: Find the value of each expression. 9P3 and10C4 • one year ago • one year ago Best Response You've already chosen the best response. nPr = n!/ (n-r)! Best Response You've already chosen the best response. nCr = n!/(r! * (n-r)! ) Best Response You've already chosen the best response. i am new to this please explain Your question is ready. Sign up for free to start getting answers. is replying to Can someone tell me what button the professor is hitting... • Teamwork 19 Teammate • Problem Solving 19 Hero • Engagement 19 Mad Hatter • You have blocked this person. • ✔ You're a fan Checking fan status... Thanks for being so helpful in mathematics. If you are getting quality help, make sure you spread the word about OpenStudy. This is the testimonial you wrote. You haven't written a testimonial for Owlfred.
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Rainbow attack Elcomsoft.com » Password Recovery Software » Proactive Password Auditor » Help Rainbow attack Previous Top Next Rainbow attack is an implementation of the Faster Cryptanalytic Time-Memory Trade-Off method developed by Dr Philippe Oechslin. The idea is to generate the password hash tables in advance (only once), and during the audit/recovery process, simply look up the hash in these pre-computed tables. Such process dramatically reduces the auditing time (especially for complex passwords). Due to the nature of this attack, not all passwords can be found (although with a probability which can be as high as needed). To access Rainbow attack settings, switch the Attack type to Rainbow, and click on the Rainbow attack tab (second tab, next to the Hashes tab). If you already have the tables, click on the Rainbow tables list button, and you will be able to browse for the tables for further attack (you can add several tables at once), remove the tables from the list, and move them up and down; when completed, press Close, and proceed with the attack itself. The program also supports indexed rainbow tables that are available at http://www.freerainbowtables.com. To create your own tables, press the Generate tables button. There are a few settings there: Hash type LM and NTLM hash tables can be generated; see About Windows passwords for details on hash types. Password length Minimum and Maximum; typically, from 1 to 7 (to cover all password space for LM hashes). However, if you want to audit just 6-character passwords (and second halves of passwords that are from 8 to 15 characters long), you can create more effective and still relatively small tables for length from 1 to 6. Available choices: •alpha: capital letters only (26) •alpha-space: capital letters plus space character (27) •alpha-numeric: capital letters plus digits (36) •alpha-numeric-space: capital letters plus digits and space character (37) •alpha-numeric-symbol14: capital letters, digits, and 14 most-common symbols: !@#$%^&*()-_+= (50) •alpha-numeric-symbol14: capital letters, digits, space and 14 most-common symbols: !@#$%^&*()-_+= (51) •all: capital letters, digits and 32 printable symbols including space (69) Chain length Typical values are from 1000 to 10000. When this value is increased, you get better probability, but worse generation and cryptanalysis times. Chain count Chain count affects the table size (and so disk space), table size, probability and generation time (but not cryptanalysis time). Number of tables and Indexes Number of tables to generate, or indexes of tables if you distribute the table generation process across a few computers. More tables you have, the better success rate is achieved. For example, if one table gives a probability of 60% (0,6), two tables will give 1 - (1 - 0,6) * (1 - 0,6) = 0,84 (84%). With three such tables, the probability is already 1 - (1 - 0,6) ^ 3 = 0,936 (93,6%). But of course, the total space also increases dramatically. Output folder Press Browse to select the folder to save generated tables to (before starting the generation process, please verify that there is enough free space there). Once all parameters are selected, PPA immediately calculates the key space (the total number of passwords in the given range; actually, it depends only on the character set and password length), disk space (size of each table multiplied by number of tables), and success probability. You can also run the benchmark: press Start, and PPA calculates the speed of your computer on these operations, and so the table precomputation time, total precomputation time, and maximum cryptanalysis time. There are some typical configurations (for LM hash type, length from 1 to 7; the time is calculated for Pentium 4 3.0GHz CPU) you can use, for example: #1 #2 #3 #4 Charset alpha alpha-numeric alpha-num-sym14 all Chain length 2,100 2,400 12,000 20,000 Chain count 8,000,000 40,000,000 40,000,000 100,000,000 Tables 5 7 13 20 Success rate 99.9% 99.9% 99.9% 99,3% Total space 640 Mb 4,480 Mb 8,320 Mb 32,000 Mb Max gen. time 17h 5d 14h 52d 332d Max analysis time 7 s 14 s 11 m 48 m The tables for first three configurations can fit into one CD, DVD (Single Layer) and DVD (Double Layer), respectively. For the last configuration (with a complete character set), they take about 32 gigabytes and need 369 days to generate (so you have to use multiple computers), but with such tables, any password can be recovered in just about an hour with 99,3% probability. Normally, it would take up to 3 weeks to recover such password using a brute-force attack. Get more information about Proactive Password Auditor Get full version of Proactive Password Auditor (c) 2009 ElcomSoft Co.Ltd.
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Z-Score Example #1 This video contains a detailed example of a statistics problem involving the use of the standardized normal curve and z-scores. Language: English Audience: College Duration: 4 minutes 52 seconds Released on: Sep 23, 2009 11:25pm Groups: Boston College Statistics & Probability Students: 10 Tags: statistics normal distribution z-score z score z-score problem normal distribution problem Hey, I'm Zach Hagopian, and I'm a sophmore majoring in Finance in the Carroll School of Management at Boston College.
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Sunpower EG-1000 Stirling Problem 3.2 - The Sunpower EG-1000 Stirling Engine/Generator This exercise concerns the ideal performance of the EG-1000 Stirling engine (developed by Sunpower, Inc) which is gas fired and has been designed to generate electricity as well as to provide hot water for a private home. This engine is shown in the figure below together with a simplified schematic diagram. Notice that there are two pistons - a power piston which allows compression and expansion of the working gas (helium) and a displacer piston which shuttles the working gas between the hot expansion space V[E] and the cold compression space V[C], through the series connected heater, regenerator and cooler. Conceptually the Stirling engine is the simplest of all heat engines. The working gas is sealed within its cylinder by the power piston. The displacer piston shuttles the gas such that the gas will compress while it is mainly in the cool compression space and expand while in the hot expansion space. Since the gas is at a higher temperature, and therefore pressure, during its expansion than during its compression, more power is produced during expansion than is reabsorbed during compression, and this net excess power is the useful output of the engine. Note that there are no valves or intermittent combustion, which is the major source of noise in an internal combustion engine. The same working gas is used over and over again, making the Stirling engine a sealed, closed cycle system. All that is added to the system is steady high temperature heat, and all that is removed from the system is low temperature heat and mechanical power. Figure 1 - The Sunpower EG-1000 free-piston Stirling engine/generator ││The linear electrical generator (not shown in the above schematic) is comprised of powerful rare-earth magnets in the piston cutting a magnetic circuit and coils in the cylinder. This produces 240│ ││Volts at 50 Herz - designed for operation in Europe, and is capable of producing more than one kilowatt of electrical power output at an efficiency of around 90%. │ ││ │ ││ │ ││The hot water is provided by operating the cooling water at a temperature of 50°C. │ Unfortunately the analysis of actual Stirling cycle machines is extremely complex and requires sophisticated computer analysis. We consider an idealized model of this engine defined in terms of the P-V diagram shown below, and will attempt to quantify the performance characteristics from this ideal model. These are the mechanical output power, the thermal efficiency, thermal power for home water heating and the effect of the regenerator on the thermal efficiency. The working gas used is helium, which has the advantage of having a low molecular weight and high thermal conductivity compared to air, allowing a high efficiency system. Process (1)-(2) is the isothermal compression of the helium at temperature T[C] = 50°C, during which heat Q[C] is rejected to the cooling water. Process (2)-(3) is the constant volume displacement process during which heat Q[R] is absorbed from the regenerator matrix. Process (3)-(4) is the power producing isothermal expansion process at temperature T[E] = 500°C, during which heat Q[E] is absorbed from the gas burner, and finally process (4)-(1) is the constant volume displacement process during which heat Q[R] is lost to the regenerator matrix. Thus the ideal Stirling cycle consists of four distinct processes, each one of which can be separately analysed in accordance with the methods that are described in Chapter 3b. State (1) is defined at a maximum volume of 650 cu.cm and a pressure of 10 bar, and State (2) is defined at a minimum volume of 550 cu.cm. This large minimum volume is the dead space due to the unswept volumes including the heater, regenerator and cooler spaces. (Note that the values presented here are not actual values of the EG-1000, however were devised by your instructor for purposes of this exercise only). Figure 2. The ideal Stirling cycle engine P-V diagram Since the Stirling cycle is a closed cycle, we can consider each process separately. Thus the work done for each process can be determined by integration. This is equivalent to evaluating the area under the P-v curve, as follows: The working fluid is helium which is an ideal gas, we use the ideal gas equation of state throughout. Thus P V = m R T, where R = 2.077 kJ/kg K, and [V] , where C[V] = 3.116 kJ/kg K. (refer: Ideal Gas Properties) 1. From the given conditions at state 1 (P = 10 bar = 1000 kPa, V = 650 cc, T = 50°C) determine the mass of working gas (helium) used in the cycle. [m = 0.00097 kg (close to 1 gm)] 2. Determine the net work done per cycle (kiloJoules): W[E] + W[C] (Note that the compression work WC is always negative). At a frequency of 50 Herz (cycles per second) determine the power output produced by the engine. [Wnet = 0.151 kJ/cycle, Power = 7.55 kW] 3. Determine the heat absorbed in the expansion space Q[E] during the expansion process (3)-(4). [Q[E] = 0.260 kJ] 4. Evaluate the Thermal Efficiency [th], defined as: [th] = (W[E] + W[C]) / Q[E]. (Net mechanical work done divided by the heat supplied externally by the gas burner). [58 %] 5. Determine the amount of thermal power rejected to the cooling water. Note that at a temperature of 50°C this is suitable for providing hot water for the home, as well as providing home space heating capability. [Q[C] = -0.109 kJ/cycle, Thermal power to cooling water = 5.45 kW] 6. Determine the amount of heat transferred to the working fluid Q[R] as it passes through the regenerator during process (2)-(3). [1.36 kJ] If this heat were to be supplied externally by the gas burner, (i.e. no regenerator) what would be the new value of thermal efficiency [th]? [9.3%] ││In this photograph we see the Sunpower EG-1000 being demonstrated using sawdust pellets as the fuel, and generating more than 1000W of electricity to a light panel. This was done at the │ ││Sustainability Fair in the Fairgrounds of Athens Ohio, 2001. A closeup photograph of the basic system is shown. Notice the closed cycle radiator and vibration pump used in the water cooling │ ││system. │ Engineering Thermodynamics by Israel Urieli is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 United States License
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CCSS.Math.Content.HSG-GPE.B.5 - Wolfram Demonstrations Project US Common Core State Standard Math HSG-GPE.B.5 Demonstrations 1 - 1 of 1 Description of Standard: Prove the slope criteria for parallel and perpendicular lines and use them to solve geometric problems (e.g., find the equation of a line parallel or perpendicular to a given line that passes through a given point).
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View high resolution This is the Google trend for the search query “Quadratic formula” It repeats in the same pattern every year. Down in summer, up in September, down again in December and up again in spring time before going down again in the summer. And so it goes on forever. The Quadratic Formula Formula.
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omplex number Complex number complex numbers are an extension of the real numbers , in which all non-constant . The complex numbers contain a number , the imaginary unit , with = −1, i.e., is a square root of −1. Every complex number can be represented in the form , where are real numbers called the real part and the imaginary part of the complex number respectively. The sum and product of two complex numbers are: Complex numbers were first introduced in connection with explicit formulas for the roots of polynomials. In mathematics, the term "complex" when used as an means that the field of complex numbers is the underlying number field considered. For example complex matrix complex polynomial complex Lie algebra The earliest fleeting reference to square roots of negative numbers occurred in the work of the Greek mathematician and inventor Heron of Alexandria in the 1st century AD, when he considered the volume of an impossible frustum of a pyramid. They became more prominent when in the 16th century closed formulas for the roots of third and fourth degree polynomials were discovered by Italian mathematicians (see Tartaglia, Cardano). It was soon realized that these formulas, even if one was only interested in real solutions, sometimes required the manipulation of square roots of negative numbers. This was doubly unsettling since not even negative numbers were considered to be on firm ground at the time. The term "imaginary" for these quantities was coined by René Descartes in the 17th century and was meant to be derogatory. (See imaginary number for a discussion of the "reality" of complex numbers.) The 18th century saw the labors of Abraham de Moivre and Leonhard Euler. To De Moivre is due (1730) the well-known formula which bears his name, de Moivre's formula: and to Euler (1748) Euler's formula of complex analysis: The existence of complex numbers was not completely accepted until the geometrical interpretation (see below) had been described by Caspar Wessel ; it was rediscovered several years later and popularized by Carl Friedrich Gauss , and as a result the theory of complex numbers received a notable expansion. The idea of the graphic representation of complex numbers had appeared, however, as early as 1685, in De Algebra tractatus Wessel's memoir appeared in the Proceedings of the Copenhagen Academy for 1799, and is exceedingly clear and complete, even in comparison with modern works. He also considers the sphere, and gives a quaternion theory from which he develops a complete spherical trigonometry. In 1804 the Abbé Buée independently came upon the same idea which Wallis had suggested, that should represent a unit line, and its negative, perpendicular to the real axis. Buée's paper was not published until 1806, in which year Jean-Robert Argand also issued a pamphlet on the same subject. It is to Argand's essay that the scientific foundation for the graphic representation of complex numbers is now generally referred. Nevertheless, in 1831 Gauss found the theory quite unknown, and in 1832 published his chief memoir on the subject, thus bringing it prominently before the mathematical world. Mention should also be made of an excellent little treatise by Mourey (1828), in which the foundations for the theory of directional numbers are scientifically laid. The general acceptance of the theory is not a little due to the labors of Cauchy and Abel, and especially the latter, who was the first to boldly use complex numbers with a success that is well known. The common terms used in the theory are chiefly due to the founders. Argand called the direction factor, and the modulus; Cauchy (1828) called the reduced form (l'expression réduite); Gauss used for , introduced the term complex number for , and called the norm. The expression direction coefficient, often used for , is due to Hankel (1867), and absolute value, for modulus, is due to Weierstrass. Following Cauchy and Gauss have come a number of contributors of high rank, of whom the following may be especially mentioned: Kummer (1844), Kronecker (1845), Scheffler (1845, 1851, 1880), Bellavitis (1835, 1852), Peacock (1845), and De Morgan (1849). Möbius must also be mentioned for his numerous memoirs on the geometric applications of complex numbers, and Dirichlet for the expansion of the theory to include primes, congruences, reciprocity, etc., as in the case of real numbers. Other types have been studied, besides the familiar , in which is the root of . Thus Eisenstein has studied the type , being a complex root of . Similarly, complex types have been derived from ( prime). This generalization is largely due to Kummer, to whom is also due the theory of Ideal numbers, which has recently been simplified by Klein (1893) from the point of view of geometry. A further complex theory is due to Galois, the basis being the imaginary roots of an irreducible congruence, (mod , a prime). The late writers (from 1884) on the general theory include , Schwarz, , Berloty, , and Macfarlane. The formally correct definition using pairs of real numbers was given in the 19th century. Formally we may define complex numbers as ordered pairs of real numbers (a, b) together with the operations: So defined, the complex numbers form a field, the complex number field, denoted by C (or in blackboard bold). We identify the real number a with the complex number (a, 0), and in this way the field of real numbers R becomes a subfield of C. The imaginary unit i is the complex number (0,1). In C, we have: • additive identity ("zero"): (0,0) • multiplicative identity ("one"): (1,0) • additive inverse of (a,b): (−a,−b) • multiplicative inverse of non-zero (a,b): could also be defined as the topological closure of algebraic numbers and the algebraic closure A complex number can also be viewed as a point or a position vector on the two dimensional Cartesian coordinate system. This representation is sometimes called an Argand diagram. In the figure, we The latter expression is sometimes shorthanded as r cis φ, where r = |z| is called the absolute value of z and φ = arg(z) is called the complex argument of z. However, Euler's formula states that e^i φ = cisφ. The exponential form gives us a better insight than the shorthand rcisφ, which is almost never used in serious mathematical articles. By simple trigonometric identities, we see that and that Now the addition of two complex numbers is just the vector addition of two vectors, and the multiplication with a fixed complex number can be seen as a simultaneous rotation and stretching. Multiplication with i corresponds to a counter clockwise rotation by 90 degrees. The geometric content of the equation i^2 = -1 is that a sequence of two 90 degree rotation results in a 180 degree rotation. Even the fact (-1) · (-1) = +1 from arithmetic can be understood geometrically as the combination of two 180 degree turns. Absolute value, conjugation and distance Recall that the absolute value (or modulus or magnitude) of a complex number z = r e^iφ is defined as |z| = r. Algebraically, if z = a + ib, then |z| = &radic(a² + b² ). One can check readily that the absolute value has three important properties: for all complex numbers z and w. By defining the distance function d(z, w) = |z - w| we turn the complex numbers into a metric space and we can therefore talk about limits and continuity. The addition, subtraction, multiplication and division of complex numbers are then continuous operations. Unless anything else is said, this is always the metric being used on the complex numbers. The complex conjugate of the complex number z = a + ib is defined to be a - ib, written as or z^*. As seen in the figure, is the "reflection" of z about the real axis. The following can be checked: if and only if z is real if z is non-zero The latter formula is the method of choice to compute the inverse of a complex number if it is given in rectangular coordinates. That conjugate commutes with all the algebraic operations (and many functions; e.g. i (-1 has two square roots); note, however, that conjugate is not differentiable (see holomorphic). The complex argument of z=re^iφ is φ. Note that the complex argument is unique modulo 2π. Matrix representation of complex numbers While usually not useful, alternative representations of complex field can give some insight into their nature. One particularly elegant representation interprets every complex number as 2×2 matrix with real entries which stretches and rotates the points of the plane. Every such matrix has the form with real numbers a and b. The sum and product of two such matrices is again of this form. Every non-zero such matrix is invertible, and its inverse is again of this form. Therefore, the matrices of this form are a field. In fact, this is exactly the field of complex numbers. Every such matrix can be written as which suggests that we should identify the real number 1 with the matrix and the imaginary unit i with a counter-clockwise rotation by 90 degrees. Note that the square of this latter matrix is indeed equal to -1. The absolute value of a complex number expressed as a matrix is equal to the square root of the determinant of that matrix. If the matrix is viewed as a transformation of a plane, then the transformation rotates points through an angle equal to the argument of the complex number and scales by a factor equal to the complex number's absolute value. The conjugate of the complex number z corresponds to the transformation which rotates through the same angle as z but in the opposite direction, and scales in the same manner as z; this can be described by the transpose of the matrix corresponding to z. Some properties Real vector space C is a two-dimensional real vector space. Unlike the reals, complex numbers cannot be ordered in any way that is compatible with its arithmetic operations: C cannot be turned into an ordered field. Solutions of polynomial equations A root of the polynomial p is a complex number z such that p(z) = 0. A most striking result is that all polynomials of degree n with real or complex coefficients have exactly n complex roots (counting multiple roots according to their multiplicity). This is known as the Fundamental Theorem of Algebra, and shows that the complex numbers are an algebraically closed field. Indeed, the complex number field is the algebraic closure of the real number field. It can be identified as the quotient ring of the polynomial ring R[X] by the ideal generated by the polynomial X^2 + 1: This is indeed a field because X^2 + 1 is irreducible. The image of X in this quotient ring becomes the imaginary unit i. Algebraic characterization The field C is (up to field isomorphism) characterized by the following three facts: Consequently, C contains many proper subfields which are isomorphic to C. Complex analysis The study of functions of a complex variable is known as complex analysis and has enormous practical use in applied mathematics as well as in other branches of mathematics. Often, the most natural proofs for statements in real analysis or even number theory employ techniques from complex analysis (see prime number theorem for an example). Unlike real functions which are commonly represented as two dimensional graphs, complex functions have four dimensional graphs and may usefully be illustrated by color coding a three dimensional graph to suggest four dimensions, or by animating the complex function's dynamic transformation of the complex plane. Control theory In control theory, systems are often transformed from the time domain to the frequency domain using the Laplace transform. The system's poles and zeros are then analyzed in the complex plane. The root locus, nyquist plot, and nichols plot techniques all make use of the complex plane. In the root locus method, it is especially important whether the poles and zeros are in the left or right half planes, i.e. have real part greater than or less than zero. If a system has poles that • in the right half plane, it will be unstable, • all in the left half plane, it will be stable, • on the imaginary axis, it will be marginally stable. If a system has zeros in the right half plane, it is a nonminimum phase system. Signal analysis Complex numbers are used in signal analysis and other fields as a convenient description for periodically varying signals. The absolute value |z| is interpreted as the amplitude and the argument arg( z) as the phase of a sine wave of given frequency. If Fourier analysis is employed to write a given real-valued signal as a sum of periodic functions, these periodic functions are often written as the real part of complex valued functions of the form where ω represents the angular frequency and the complex number z encodes the phase and amplitude as explained above. In electrical engineering, this is done for varying voltages and currentss. The treatment of resistors, capacitors and inductors can then be unified by introducing imaginary frequency-dependent resistances for the latter two and combining all three in a single complex number called the impedance. (Electrical engineers and some physicists use the letter j for the imaginary unit since i is typically reserved for varying currents.) Improper integrals The residue theorem of complex analysis is often used in applied fields to compute certain improper integrals. See examples of contour integration. Quantum mechanics The complex number field is also of utmost importance in quantum mechanics since the underlying theory is built on (infinite dimensional) Hilbert spaces over C. In Special and general relativity, some formulas for the metric on spacetime become simpler if one takes the time variable to be imaginary. Applied mathematics In differential equations, it is common to first find all complex roots r of the characteristic equation of a linear differential equation and then attempt to solve the system in terms of base functions of the form f(t) = e^rt. Fluid dynamics In fluid dynamics, complex functions are used to describe potential flow in 2d. Certain fractals employ complex numbers in the plotting of their function, e.g. Mandelbrot set and Lyapunov fractal. See also quaternions, complex geometry, local fields, phasors, Leonhard Euler, Euler's identity, Hypercomplex number, De Moivre's formula, Further reading • An Imaginary Tale, by Paul J. Nahin; Princeton University Press; ISBN 0691027951 (hardcover, 1998). A gentle introduction to the history of complex numbers and the beginnings of complex analysis. Topics in mathematics related to quantity Edit Numbers | Natural numbers | Integers | Rational numbers | Real numbers | Complex numbers | Hypercomplex numbers | Quaternions | Octonions | Sedenions | Hyperreal numbers | Surreal numbers | Ordinal numbers | Cardinal numbers | p-adic numberss | Integer sequences | Mathematical constants | Infinity Topics in mathematics related to spaces Edit Topology | Geometry | Trigonometry | Algebraic geometry | Differential geometry and topology | Algebraic topology | Linear algebra | Fractal geometry | Compact space
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TI Math Nspired • Students will recognize that the correlation coefficient describes the strength and direction of the linear association between two variables. • Students will recognize that when two variables are highly linearly correlated, their correlation coefficient will be close to , and when they have little correlation, the correlation coefficient will be close to 0. • Students will recognize that two variables with a high correlation coefficient might have a scatterplot that displays a nonlinear pattern. • Students will recognize that correlation is not affected by the choice of x or y, that is, by the choice of which variable is explanatory and which is response. • Students will make sense of problems and persevere in solving them (CCSS Mathematical Practices). • Students will reason abstractly and quantitatively (CCSS Mathematical Practices). • correlation coefficient • explanatory variable • linear • outlier • response variable • scatterplot About the Lesson This lesson involves investigating the connection between the scatterplot of bivariate data and the numerical value of the correlation coefficient. As a result, students will: • Consider a scatterplot of points that lie in a straight line and one whose points do not line in a straight line and interpret the correlation coefficient for each plot. • Look at pairs of scatterplots to estimate which plot has the higher correlation coefficient. • Move points to try to match a given correlation coefficient. • Investigate a plot of ordered pairs and a plot of the inverse relation by inspecting the coordinates of the points and, by dragging the points in either plot, observing that the correlation coefficients are the same for both plots.
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High Frequency and Microwave Engineering This book is dedicated to my wife, for her help and encouragement in the writing of this book High Frequency and Microwave Engineering E. da Silva The Open University OXFORD AUCKLAND BOSTON JOHANNESBURG MELBOURNE NEW DELHI Linacre House, Jordan Hill, Oxford OX2 8DP 225 Wildwood Avenue, Woburn, MA 01801-2041 A division of Reed Educational and Professional Publishing Ltd A member of the Reed Elsevier plc group First published 2001 © E. da Silva 2001 All rights reserved. No part of this publication may be reproduced or transmitted in any form or by any means, electronically or mechanically, including photocopying, recording or any information storage or retrieval system, without either prior permission in writing from the publisher or a licence permitting restricted copying. In the United Kingdom such licences are issued by the Copyright Licensing Agency: 90 Tottenham Court Road, London W1P 0LP. Whilst the advice and information in this book are believed to be true and accurate at the date of going to press, neither the author[s] nor the publisher can accept any legal responsibility or liability for any errors or omissions that may be made. British Library Cataloguing in Publication Data A catalogue record for this book is available from the British Library ISBN 0 7506 5646 X Typeset in 10/12 pt Times by Cambrian Typesetters, Frimley, Surrey Printed and bound by MPG Books Ltd, Bodmin, Cornwall Preface ix 1 BASIC FEATURES OF RADIO COMMUNICATION SYSTEMS 1 1.1 Introduction 1 1.2 Radio communication systems 2 1.3 Modulation and demodulation 3 1.4 Radio wave propagation techniques 9 1.5 Antennas and Aerials 14 1.6 Antenna arrays 23 1.7 Antenna distribution systems 25 1.8 Radio receivers 32 1.9 Radio receiver properties 33 1.10 Types of receivers 37 1.11 Summary 41 2 TRANSMISSION LINES 43 2.1 Introduction 43 2.2 Transmission line basics 45 2.3 Types of electrical transmission lines 47 2.4 Line characteristic impedances and physical parameters 50 2.5 Characteristic impedance (Z0) from primary electrical parameters 54 2.6 Characteristic impedance (Z0) by measurement 58 2.7 Typical commercial cable impedances 60 2.8 Signal propagation on transmission lines 61 2.9 Waveform distortion and frequency dispersion 63 2.10 Transmission lines of finite length 64 2.11 Reflection and transmission coefficients 64 2.12 Propagation constant (γ) of transmission lines 72 2.13 Transmission lines as electrical components 77 2.14 Transmission line couplers 82 2.15 Summary 98 3 SMITH CHARTS AND SCATTERING PARAMETERS 88 3.1 Introduction 88 3.2 Smith charts 89 vi Contents 3.3 The immittance Smith chart 97 3.4 Admittance manipulation on the chart 98 3.5 Smith chart theory and applications 98 3.6 Reflection coefficients and impedance networks 102 3.7 Impedance of distributed circuits 106 3.8 Impedance matching 110 3.9 Summary of Smith charts 125 3.10 Scattering parameters (s-parameters) 125 3.11 Applied examples of s-parameters in two port networks 131 3.12 Summary of scattering parameters 140 4 PUFF SOFTWARE 142 4.1 Introduction 142 4.2 CalTech’s PUFF Version 2.1 143 4.3 Installation of PUFF 143 4.4 Running PUFF 144 4.5 Examples 147 4.6 Bandpass filter 152 4.7 PUFF commands 156 4.8 Templates 157 4.9 Modification of transistor templates 163 4.10 Verification of some examples given in Chapters 2 and 3 165 4.11 Using PUFF to evaluate couplers 170 4.12 Verification of Smith chart applications 172 4.13 Verification of stub matching 176 4.14 Scattering parameters 186 4.15 Discontinuities: physical and electrical line lengths 189 4.16 Summary 192 5 AMPLIFIER BASICS 195 5.1 Introduction 195 5.2 Tuned circuits 196 5.3 Filter design 202 5.4 Butterworth filter 208 5.5 Tchebyscheff filter 224 5.6 Summary on filters 231 5.7 Impedance matching 232 5.8 Three element matching networks 252 5.9 Broadband matching networks 259 5.10 Summary of matching networks 261 6 HIGH FREQUENCY TRANSISTOR AMPLIFIERS 262 6.1 Introduction 262 6.2 Bi-polar transistors 262 6.3 Review of field effect transistors 277 6.4 A.C. equivalent circuits of transistors 291 6.5 General r.f. design considerations 304 Contents vii 6.6 Transistor operating configurations 316 6.7 Summary 319 7 MICROWAVE AMPLIFIERS 320 7.1 Introduction 320 7.2 Transistors and s-parameters 321 7.3 Design of amplifiers with conjugately matched impedances 322 7.4 Design of amplifiers for a specific gain 332 7.5 Design of amplifiers for optimum noise figure 345 7.6 Design of broadband amplifiers 349 7.7 Feedback amplifiers 352 7.8 R.F. power transistors 355 7.9 Summary 35S 8 OSCILLATORS AND FREQUENCY SYNTHESISERS 357 8.1 Introduction 357 8.2 Sine wave type oscillators 358 8.3 Low frequency sine wave oscillators 361 8.4 Wien bridge oscillator 361 8.5 Phase shift oscillators 364 8.6 Radio frequency (LC) oscillators 368 8.7 Colpitts oscillator 368 8.8 Hartley oscillator 371 8.9 Clapp oscillator 372 8.10 Voltage-controlled oscillator 375 8.11 Comparison of the Hartley, Colpitts, Clapp and voltage-controlled oscillators 376 8.12 Crystal control oscillators 376 8.13 Phase lock loops 380 8.14 Frequency synthesisers 393 8.15 Summary 399 9 FURTHER TOPICS 400 9.1 Aims 400 9.2 Signal flow graph analysis 400 9.3 Small effective microwave CAD packages 410 9.4 Summary of software 420 References 421 Index 000 This book was started while the author was Professor and Head of Department at Etisalat College which was set up with the technical expertise of the University of Bradford, England. It was continued when the author returned to the Open University, England. Many thanks are due to my colleagues Dr David Crecraft and Dr Mike Meade of the Open University, Dr L. Auchterlonie of Newcastle University and Dr N. McEwan and Dr D. Dernikas of Bradford University. I would also like to thank my students for their many helpful comments. High Frequency and Microwave Engineering has been written with a view to ease of understanding and to provide knowledge for any engineer who is interested in high frequency and microwave engineering. The book has been set at the third level standard of an electrical engineering degree but it is eminently suitable for self-study. The book comprises standard text which is emphasised with over 325 illustrations. A further 120 examples are given to emphasise clarity in understanding and application of important A software computer-aided-design package, PUFF 2.1 produced by California Institute of Technology (CalTech) U.S.A., is supplied free with the book. PUFF can be used to provide scaled layouts and artwork for designs. PUFF can also be used to calculate the scattering parameters of circuits. Up to four scattering parameters can be plotted simulta- neously and automatically on a Smith chart as well as in graphical form. In addition to the PUFF software I have also included 42 software application examples. These examples have been chosen to calculate and verify some of the examples given in the text, but many are proven designs suitable for use in practical circuits. The confirmation of manual design and CAD design is highly gratifying to the reader and it helps to promote greater confi- dence in the use of other types of software. An article ‘Practical Circuit Design’ explain- ing how PUFF can be used for producing layout and artwork for circuits is explained in detail. There is also a detailed microwave amplifier design which uses PUFF to verify circuit calculations, match line impedances, and produce the artwork for amplifier fabri- cation. There is also a copy of CalTech’s manual on disk. This will prove useful for more advanced work. The book commences with an explanation of the many terms used in radio, wireless, high frequency and microwave engineering. These are explained in Chapter 1. Chapter 2 provides a gentle introduction to the subject of transmission lines. It starts with a gradual introduction of transmission lines by using an everyday example. Diagrams have been x Preface used to illustrate some of the characteristics of transmission lines. Mathematics has been kept to a minimum. The chapter ends with some applications of transmission lines espe- cially in their use as inductors, capacitors, transformers and couplers. Chapter 3 provides an introduction to Smith charts and scattering parameters. Smith charts are essential in understanding and reading manufacturers’ data because they also provide a ‘picture’ of circuit behaviour. Use of the Smith chart is encouraged and many examples are provided for the evaluation and manipulation of reflection coefficients, impedance, admittance and matching circuits. For those who want it, Smith chart theory is presented, but it is stressed that knowledge of the theory is not essential to its use. The installation of PUFF software is introduced in Chapter 4. The chapter goes on to deal with the printing and fabrication of artwork and the use and modification of templates. Particular attention is paid to circuit configurations including couplers, transformers and matching of circuits. Scattering parameters are re-introduced and used for solving scatter- ing problems. Many of the examples in this chapter are used to confirm the results of the examples given in Chapters 2 and 3. Amplifier circuitry components are dealt with in Chapter 5. Particular attention is paid to the design of Butterworth and Tchebyscheff filters and their uses as low pass, bandpass, high pass and bandstop filters. Impedance matching is discussed in detail and many meth- ods of matching are shown in examples. Chapter 6 deals with the design of amplifiers including transistor biasing which is vitally important for it ensures the constancy of transistor parameters with temperature. Examples are given of amplifier circuits using unconditionally stable transistors and condi- tionally stable amplifiers. The use of the indefinite matrix in transistor configurations is shown by examples. The design of microwave amplifiers is shown in Chapter 7. Design examples include conjugately matched amplifiers, constant gain amplifiers, low noise amplifiers, broadband amplifiers, feedback amplifiers and r.f. power amplifiers. Oscillators and frequency synthesizers are discussed in Chapter 8. Conditions for oscil- lation are discussed and the Barkhausen criteria for oscillation is detailed in the early part of the chapter. Oscillator designs include the Wien bridge, phase shift, Hartley, Colpitts, Clapp, crystal and the phase lock loop system. Frequency synthesizers are discussed with reference to direct and indirect methods of frequency synthesis. Chapter 9 is a discussion of topics which will prove useful in future studies. These include signal flow diagrams and the use of software particularly the quasi-free types. Comments are made regarding the usefulness of Hewlett Packard’s AppCAD and Motorola’s impedance matching program, MIMP. Finally, I wish you well in your progress towards the fascinating subject of high frequency and microwave engineering. Ed da Silva Basic features of radio communication systems 1.1 Introduction This chapter describes communication systems which use radio waves and signals. Radio signals are useful for two main reasons. They provide a relatively cheap way of commu- nicating over vast distances and they are extremely useful for mobile communications where the use of cables is impractical. Radio signals are generally considered to be electromagnetic signals which are broad- cast or radiated through space. They vary in frequency from several kilohertz1 to well over 100 GHz (1011 Hz). They include some well known public broadcasting bands: long-wave (155–280 kHz), medium-wave (522–1622 kHz), short-wave (3–30 MHz), very high frequency FM band (88–108 MHz), ultra high frequency television band (470–890 MHz) and the satellite television band (11.6 to 12.4 GHz). The frequencies2 quoted above are approximate figures and are only provided to give an indication of some of the frequency bands used in Radio and TV broadcasting. 1.1.1 Aims The aims of this chapter are to introduce you to some basic radio communications princi- ples and methods. These include modulation (impressing signal information on to radio carrier waves), propagation (transmission of radio carrier waves) and demodulation (detection of radio carrier waves) to recover the original signal information. The method we use here is to start with an overview of a communication system. The system is then divided to show its sub-systems and the sub-systems are then expanded to show individual circuits and items. 1.1.2 Objectives The general objectives of this chapter are: • to help you understand why certain methods and techniques are used for radio frequency and high frequency communication circuits; 1 One hertz (Hz) means 1 cyclic vibration per second: 1 kHz = 1000 cyclic vibrations per second, 1 MHz = 1 000 000 cyclic vibrations per second, and 1 GHz = 1 000 000 000 cyclic vibrations per second. The word Hertz is named after Heinrich Hertz, one of the early pioneers of physics. 2 The frequencies quoted are for Europe. Other countries do not necessarily follow the exact same frequen- cies but they do have similar frequency bands. 2 Basic features of radio communication systems • to appreciate the need for modulation; • to understand the basic principles of modulation and demodulation; • to understand the basic principles of signal propagation using antennas; • to introduce radio receivers; • to introduce you to the requirements of selectivity and bandwidth in radio communica- tion circuits. 1.2 Radio communication systems 1.2.1 Stages in communication Let’s commence with a simple communications example and analyse the important stages necessary for communication. This is shown diagramatically in Figure 1.1. We start by writing a letter-message, putting it in an envelope, and sending it through a post-carrier (postal carrier system) to our destination. At the other end, our recipient receives the letter from the post office, opens the envelope and reads our message. Why do we carry out these We write a letter because it contains the information we want to send to our recipient. In radio communications, we do the same thing; we use a message signal, which is an elec- trical signal derived from analogue sound or digitally encoded sound and/or video/data signals, as the information we want to convey. The process of putting this information into an ‘envelope’ for transmission through the carrier is called modulation and circuits designed for this purpose are known as modulation circuits or modulators. We use the post office as the carrier for our letters because the post office has the abil- ity to transmit messages over long distances. In radio communications, we use a radio frequency carrier because a radio carrier has the ability to carry messages over long distances. A radio frequency carrier with an enveloped message impressed on it is often called an enveloped carrier wave or a modulated carrier wave. When the post office delivers a letter to a destination, the envelope must be opened to enable the message to be read. In radio communications when the enveloped carrier wave Fig. 1.1 Analogy between the postal system and a radio system Modulation and demodulation 3 arrives at its destination, the enveloped carrier must be ‘opened’ or demodulated to recover the original message from the carrier. Circuits which perform this function are known as demodulation circuits or demodulators. The post office uses a system of postal codes and addresses to ensure that a letter is selected and delivered to the correct address. In radio communications, selective or tuned circuits are used to select the correct messages for a particular receiver. Amplifiers are also used to ensure that the signals sent and received have sufficient amplitudes to operate the message reading devices such as a loudspeaker and/or a video screen. In addition to the main functions mentioned above, we need a post box to send our letter. The electrical equivalent of this is the transmitting antenna. We require a letter box at home to receive letters. The electrical equivalent of this is the receiving antenna. 1.2.2 Summary of radio communications systems A pictorial summary of the above actions is shown in Figure 1.1. There are three main functions in a radio communications system. These are: modulation, transmission and demodulation. There are also supplementary functions in a radio communications system. These include transmitting antennas,3 receiving antennas, selective circuits, and amplifiers. We will now describe these methods in the same order but with more 1.3 Modulation and demodulation Before discussing modulation and demodulation, it is necessary to clarify two points: the modulation information and the modulation method. In the case of a letter in the postal system, we are free to write our messages (modula- tion information) in any language, such as English, German, French, pictures, data, etc. However, our recipient must be able to read the language we use. For example it is useless to write our message in Japanese if our recipient can only read German. Hence the modu- lation information system we use at the transmitter must be compatible with the demod- ulation information system at the receiver. Secondly, the method of putting information (modulation method) on the letter is important. For example, we can type, use a pencil, ultra violet ink, etc. However, the reader must be able to decipher (demodulate) the information provided. For example, if we use ultra violet ink, the reader must also use ultra violet light to decipher (demodulate) the message. Hence the modulation and demodulation methods must also be compatible. In the discussions that follow we are only discussing modulation and demodulation methods; not the modulation information. We also tend to use sinusoidal waves for our explanation. This is because a great mathematician, Joseph Fourier,4 has shown that peri- odic waveforms of any shape consist of one or more d.c. levels, sine waves and cosine waves. This is similar to the case in the English language, where we have thousands of words but, when analysed, all come from the 26 letters of the alphabet. Hence, the sinu- soidal wave is a useful tool for understanding modulation methods. 3 Antennas are also known as aerials. 4 Fourier analysis will be explained fully in a later section. 4 Basic features of radio communication systems Fig. 1.2 A sinusoidal radio carrier wave We now return to our simple radio carrier wave which is the sinusoidal wave5 shown in Figure 1.2. A sinusoidal wave can be described by the expression vc = Vc cos (ωct + fc) (1.1) vc = instantaneous carrier amplitude (volts) Vc = carrier amplitude (peak volts) ωc = angular frequency in radians and ωc = 2πf c where f c = carrier frequency (hertz) φc = carrier phase delay (radians) If you look at Figure 1.2, you can see that a sinusoidal wave on its own provides little information other than its presence or its absence. So we must find some method of modu- lating our information on to the radio carrier wave. We can change: • its amplitude (Vc) according to our information – this is called amplitude modulation and will be described in Section 1.3.1; • its frequency (ωc) according to our information – this is called frequency modulation and will be described in Section 1.3.2; • its phase (φc) according to our information – this is known as phase modulation and will be described in Section 1.3.3; • or we can use a combination of one or more of the methods described above – this method is favoured by digital modulation. 1.3.1 Amplitude modulation (AM) This is the method used in medium-wave and short-wave radio broadcasting. Figure 1.3 shows what happens when we apply amplitude modulation to a sinusoidal carrier wave. 5 A sinusoidal wave is a generic name for a sine or cosine wave. In many cases, cosine waves are used because of ease in mathematical manipulation. Modulation and demodulation 5 Fig. 1.3 Amplitude modulation waveforms: (a) modulating wave; (b) carrier wave; (c) modulated wave Figure 1.3(a) shows the modulating wave on its own.6 Figure 1.3(b) shows the carrier wave on its own. Figure 1.3(c) shows the resultant wave. The resultant wave shape is due to the fact that at times the modulating wave and the carrier wave are adding (in phase) and at other times, the two waves are opposing each other (out of phase). Amplitude modulation can also be easily analysed mathematically. Let the sinusoidal modulating wave be described as 6 I have used a cosine wave here because you will see later when we use Fourier analysis that waveforms, no matter how complicated, can be resolved into a series of d.c., sine and cosine terms and their harmonics. 6 Basic features of radio communication systems vm = Vm cos (ωmt) (1.2) vm = instantaneous modulating amplitude (volts) Vm = modulating amplitude (peak volts) ωm = angular frequency in radians and ωm = 2πf m where fm = modulating frequency (hertz) When the amplitude of the carrier is made to vary about Vc by the message signal vm, the modulated signal amplitude becomes [Vc + Vm cos (ωmt)] (1.3) The resulting envelope AM signal is then described by substituting Equation 1.3 into Equation 1.1 which yields [Vc + Vm cos (ωmt)] cos (ωct + φc) (1.4) It can be shown that when this equation is expanded, there are three frequencies, namely (f c – f m), f c and (f c + f m). Frequencies (f c – f m) and (f c + f m) are called sideband frequen- cies. These are shown pictorially in Figure 1.4. Fig. 1.4 Frequency spectrum of an AM wave The modulating information is contained in one of the sideband frequencies which must be present to extract the original message. The bandwidth (bw) is defined as the highest frequency minus the lowest frequency. In this case, it is (f c + f m) – (f c – f m) = 2f m where f m is the highest modulation frequency. Hence, a radio receiver must be able to accommo- date the bandwidth of a signal.7 1.3.2 Frequency modulation (FM) Frequency modulation is the modulation method used in VHF radio broadcasting. Figure 1.5 shows what happens when we apply frequency modulation to a sinusoidal carrier wave. Figure 1.5(a) shows the modulating wave on its own. Figure 1.5(b) shows the carrier wave on its own. Figure 1.5(c) shows the resultant wave. The resultant wave shape is due to the 7 This is not unusual because speech or music also have low notes and high notes and to hear them our own ears (receivers) must be able to accommodate their bandwidth. Older people tend to lose this bandwidth and often are unable to hear the high notes. Modulation and demodulation 7 Fig. 1.5 Frequency modulation waveforms: (a) modulating wave; (b) carrier wave; (c) FM wave fact that the carrier wave frequency increases when the modulating signal is positive and decreases when the modulating signal is negative. Note that in pure FM, the amplitude of the carrier wave is not altered. The frequency deviation (∆f c) of the carrier is defined as [f c (max) – f c (min)] or ∆f c = f c (max) – f c (min) (1.5) According to Carson’s rule, the frequency bandwidth required for wideband FM is approx- imately 2 × (maximum frequency deviation + highest frequency present in the message signal) or bw = 2 [∆f c + f m (max)] (1.6) In FM radio broadcasting, the allocated channel bandwidth is about 200 kHz. 8 Basic features of radio communication systems Fig. 1.6 Phase modulation waveforms: (a) modulating wave; (b) carrier wave; (c) modulated wave 1.3.3 Phase modulation (PM) Phase modulation is particularly useful for digital waveforms. Figure 1.6 shows what happens when we apply phase modulation to a sinusoidal carrier wave. Figure 1.6(a) shows a digital modulating wave on its own. We have used a pulse waveform as opposed to a sine wave in this instance because it demonstrates phase modulation more clearly. Figure 1.6(b) shows the carrier wave on its own. Figure 1.6(c) shows the resultant wave. Note particularly how the phase of the carrier waveform changes when a positive modu- lating voltage is applied. In this particular case, we have shown you a phase change of 180°, but smaller phase changes are also possible. Phase modulation is popularly used for digital signals. Phase modulation is synony- mous with frequency modulation in many ways because an instantaneous change in phase8 is also an instantaneous change in frequency and vice-versa. Hence, much of what is said about FM also applies to PM. 8 Phase (φ) = angular velocity (ω) multiplied by time (t). Hence φ = ωt. Note this equation is similar to that of distance = velocity × time. This is because φ = amount of angle travelled = velocity (ω) × time (t). Radio wave propagation techniques 9 Fig. 1.7 An eight level coded signal modulated on to a radio carrier 1.3.4 Combined modulation methods Digital signals are often modulated on to a radio carrier using both phase and amplitude modulation. For example, an eight level coded digital signal can be modulated on to a carrier by using distinct 90° phase changes and two amplitude levels. This is shown diagrammatically in Figure 1.7 where eight different signals, points A to H, are encoded on to a radio carrier. This method is also known as quadrature amplitude modulation (QAM). 1.3.5 Summary of modulation systems In this section, we have shown you four methods by which information signals can be modulated on to a radio carrier. 1.4 Radio wave propagation techniques 1.4.1 Properties of electromagnetic waves In Figure 1.8 we show the case of a radio generator feeding energy into a load via a two wire transmission line. The radio generator causes voltage and current waves to flow towards the load. A voltage wave produces a voltage or electric field. A current wave produces a cuurent or magnetic field. Taken together these two fields produce an electro- magnetic field which at any instant varies in intensity along the length of the line. The electromagnetic field pattern is, however, far from stationary. Like the voltage on the line, it propagates from end to end with finite velocity which – for an air spaced line – is close to the velocity of light in free space.9 The flow of power from source to 9 Strictly speaking ‘free space’ is a vacuum. However, the velocity of propagation of electro-magnetic waves in the atmosphere is practically the same as that in a vacuum and is approximately 3 × 108 metres per second. Wavelength (λ) is defined as the ratio, velocity/frequency. 10 Basic features of radio communication systems Fig. 1.8 Energy propagation in a transmission line load is then regarded as that of an electromagnetic wave propagating between the The equivalence between the circuit and field descriptions of waves on transmission lines is demonstrated by the fact that at any point in the electromagnetic field the instan- taneous values of the electric field (E) (volts/metre) and the magnetic field (H) (amperes/metre) are related by ———— = Z0 (ohms) (1.7) where Z0 is the characteristic impedance of the transmission line.10 It can also be shown that both approaches give identical results for the power flow along a matched In the two wire transmission line shown in Figure 1.8, the parallel conductors produce electromagnetic fields which overlap and cancel in the space beyond the conductors. The radio frequency energy is thus confined and guided by the conductors from the source to its destination. If, however, the conductor spacing is increased so that it becomes com- parable with the wavelength of operation the line will begin to radiate r.f. energy to its surroundings. The energy is lost in the form of free-space electromagnetic waves which radiate away from the line with the velocity of light. The 19th century mathematician James Clerk Maxwell was the first to recognise that electromagnetic waves can exist and transport energy quite independently of any system of conductors. We know now that radio waves, heat waves, visible light, X-rays are all electromagnetic waves differing only in frequency. Figure 1.9 shows the range of frequen- cies and the regions occupied by the different types of radiation. This is known as the elec- tromagnetic spectrum. Fig. 1.9 The electromagnetic frequency spectrum 10 Transmission lines have impedances because they are constructed from physical components which have resistance, self inductance, conductance and capacitance. Radio wave propagation techniques 11 1.4.2 Free-space radiation At operational frequencies, where the operational wavelengths are comparable in size to circuit components,11 any circuit consisting of components connected by conductors will tend to act as an imperfect transmission line. As a result, there will always be some loss of r.f. energy by way of radiation. In other words, the circuit will tend to behave like a crude radio transmitter antenna. It follows that for minimal radiation, components should be small with respect to their operational wavelengths. Conversely, if radiation is desired, then the physical components should be large, approximately 1/4 wavelength for optimum radiation. This is why anten- nas are physically large in comparison with their operational wavelength. Energy radiates from an r.f. source or transmitter in all directions. If you imagine a spherical surface surrounding the transmitter, then the interior of the surface would be ‘illuminated’ with radiated energy, just like the inside of a globular lamp-shade. The illu- mination is not necessarily uniform, however, since all transmitters are, to some extent, If the r.f. source is sinusoidal, then the electric and magnetic fields will also be varying sinusoidally at any point in the radiation field. Now it is difficult to depict a propagating elec- tromagnetic field but some of its important properties can be identified. To do this we consider propagation in a particular direction on a straight line connecting a transmitter to a distant receiver as shown in Figure 1.10. You will see that this line coincides with the z-direc- tion in Figure 1.10. Measurements at the radio receiver would then indicate that the oscillat- ing electric field is acting all in one direction, the x-direction in Figure 1.10. The magnetic field is in-phase with the electric field but acts at right-angles to the electric field, in the y- direction. The two fields are thus at right-angles to each other and to the direction of propa- gation. An electromagnetic wave with these characteristics is known as a plane wave. Fig. 1.10 Electric and magnetic field directions for an electromagnetic wave propagating in the z-direction 11 Generally taken to be the case when the operational wavelength is about 1/20 of the physical size of compo- 12 Basic features of radio communication systems Provided there is no disturbance in the propagation path, the electric and magnetic field orientations with respect to the earth’s surface will remain unchanged. By convention, the orientation of the electric field with respect to the earth’s surface is called the polarisation of the electromagnetic wave. If the electric field is vertical, the wave is said to be verti- cally polarised; if horizontal, the wave is horizontally polarised. A wave is circularly polarised if its electric field rotates as the wave travels. Circular polarisation can be either clockwise or anti-clockwise. Polarisation is important because antennas must be mounted in the correct plane for optimum signal reception.12 Terrestrial broadcasting stations tend to use either vertical or horizontal polarisation. Satellite broadcasting stations use circular polarisation. The polar- isation of a wave is sometimes ‘twisted’ as it propagates through space. This twisting is caused by interfering electric or magnetic fields. It is particularly noticeable near steel- structured buildings where aerials are mounted at odd angles to the vertical and horizontal planes to compensate for these effects. Field strength The strength of a radio wave can be expressed in terms of the strength of its electric field or by the strength of its magnetic field. You should recall that these are measured in units of volts per metre and amperes per metre respectively. For a sinusoidally vary- ing field it is customary to quote r.m.s. values E rms and H rms. What is the physical significance of E rms? This is numerically equal to the r.m.s. voltage induced in a conductor of length 1 m when a perpendicular electromagnetic wave sweeps over the conductor with the velocity of light. As stated earlier, the electric and magnetic fields in a plane wave are everywhere in phase. The ratio of the field strengths is always the same and is given by electric field strength Erms ( V m ) = 377Ω (1.8) magnetic field strength Hrms ( A m ) This ratio is called the free-space wave impedance. It is analogous to the characteristic impedance of a transmission line. Example 1.1 The electric field strength at a receiving station is measured and found to have an r.m.s value of 10 microvolts/m. Calculate (a) the magnetic field strength; (b) the amount of power incident on a receiving aerial with an effective area of 5 m2. Given: Electric field strength = 10 microvolts/m. Required: (a) Magnetic field strength, (b) incident power on a receiving aerial with effec- tive area of 5 m2. 12 You can see this effect by looking at TV aerials mounted on houses. In some districts, you will see aerials mounted horizontally whilst in other areas you will find aerials mounted vertically. As a general rule, TV broad- casting authorities favour horizontal polarisation for main stations and vertical polarisation for sub or relay Radio wave propagation techniques 13 Solution. Using equation 1.8 (a) Hrms = 10 µV/m/377 Ω = 2.65 × 10–8 A/m (b) Power density is given by Erms × Hrms = 10 × 10–6 × 2.65 × 10–8 W/m2 = 2.65 × 10–13 W/m2 This is the amount of power incident on a surface of area 1 m2. For an aerial with area 5 m2, the total incident power will be P = 2.65 × 10–13 W/m2 × 5 m2 = 1.33 pW Power density The product Erms × Hrms has the dimensions of ‘volts per metre’ times ‘amps per metre’, giving watts per square metre. This is equivalent to the amount of r.f. power flowing through one square metre of area perpendicular to the direction of propagation and is known as the power density of the wave. The power density measures the intensity of the ‘illumination’ falling on a receiving aerial. A plane wave expands outwards as it travels through space from a point source. As a result, the power density falls off with increasing distance from the source. If you have studied any optics then you will be familiar with the idea that the power density falls off as the square of the distance from the source, i.e. PD2 ⎡ D1 ⎤ =⎢ ⎥ (1.9) PD1 ⎣ D2 ⎦ where P D1, P D2 = power densities at distances D 1 and D 2 respectively. Example 1.2 If the data in Example 1.1 applies to a receiver located 10 km from the transmitter, what will be the values of E rms and H rms at a distance of 100 km? Given: Data of Example 1.1 applied to a receiver at 10 km from transmitter. Required: (a) E rms at 100 km, (b) Hrms at 100 km. Solution. Using Equation 1.9 at a distance of 100 km, the power density will be reduced by a factor (10/100)2 = 0.01, so power density = 2.65 × 10–15 W/m2. Now, power density = E rms × H rms and since H rms = E rms/377 (Equation 1.7) = 2.65 × 10 −15 W m 2 Erms = 2.65 × 10 −15 × 377 = 1 µV m Hrms = 1 µV/m/377 Ω = 2.65 × 10–9 A/m 14 Basic features of radio communication systems Summary of propagation principles Several important points have been established in Section 1.4. • R.F. energy is radiated by way of travelling electric and magnetic fields which together constitute an electromagnetic wave propagating in free space with the velocity of light. • In a plane wave, the electric and magnetic fields vary in phase and act at right-angles to each other. Both fields are at right-angles to the direction of propagation. • The direction of the electric field determines the polarisation of a plane wave. • At any point, the ratio of the electric and magnetic fields is the same and equal to the wave impedance. This impedance is 377 W approximately. • The product Erms × Hrms gives the power density of the wave. • The power density falls off as the square of the distance from the r.f. source. • To obtain optimum signal reception from free space a receiving aerial should be set for the correct polarisation and be suitably located with regard to height and direction. 1.5 Antennas and aerials 1.5.1 Introduction An antenna or aerial is a structure, usually made from good conducting material, that has been designed to have a shape and size so that it will provide an efficient means of trans- mitting or receiving electromagnetic signals through free space. Many of the principles used in the construction of antennas can be easily understood by analogy to the headlamp of your car (see Figure 1.11). An isotropic light source is a light source which radiates light equally in all directions. The radiation pattern from an isotropic light source can be altered by placing a reflecting mirror on one side of the light source. This is carried out in car headlamps where a quasi- parabolic reflecting mirror (reflector) is placed behind a bulb to increase the light intensity of the lamp in the forward direction. The reflector has therefore produced a change in the directivity of the light source. The increase or ‘gain’ of light intensity in the forward direc- tion has been gained at the expense of losing light at the back of the lamp. This gain is not a ‘true gain’ because total light energy from the lamp has not been increased; light energy has only been re-directed to produce an intensity gain in the forward direction. Fig. 1.11 Radiation patterns from a car headlamp: (a) top view; (b) side view Antennas and aerials 15 The forward light intensity of a car lamp can be further improved by using one or more lenses to concentrate its forward light into a main beam or main lobe. Again, this ‘gain’ in light intensity has been achieved by confining the available light into a narrower beam of illumination; there has been no overall gain in light output from the bulb. There are also optimum sizes and distances for the placement of reflectors and lenses. These are dictated by the physical size of the bulb, the desired gain intensity of the main beam or main lobe, the required width of the main beam and the requirement to suppress minor or spurious light lobes which consume energy and cause unnecessary glare to on- coming motorists. A car headlamp (Figure 1.11) has two main light-emitting patterns; a horizontal pattern and a vertical pattern. The horizontal pattern (Figure 1.11(a)) is a bird’s eye view of the illumination pattern. A plot of the horizontal pattern is called a polar diagram. The verti- cal or azimuth pattern (Figure 1.11(b)) is the pattern seen by an observer standing to one side of the lamp. The vertical pattern is sometimes called the end-fire pattern. Both light patterns must be considered because modern headlamp reflectors tend to be elliptical and affect emitted light in the horizontal and vertical planes differently. In the above description, light has been assumed to travel from bulb to free space but the effect is equally true for light travelling in the opposite direction, i.e. the system is bi- directional. It can be used either for transmitting light from the bulb or for receiving exter- nal light at the point source usually occupied by the bulb filament. This can be easily verified by shining an external light source through the lens and the reflector in the oppo- site direction from which light had emerged, and seeing it converge on the bulb source.13 Many of the principles introduced above apply to antennas as well. Because of its bi- directional properties, a radio antenna can be used for transmitting or receiving signals. 1.5.2 Radiating resistance The relationship, power (watts) = (volts2/ohms), is used for calculating power loss in a circuit. It is not always possible to apply this law directly to a radiating circuit because a physical resistor does not always exist. Yet we cannot deny that there is a radiated power loss when a voltage is applied across a radiating circuit. To overcome this problem, engineers postulate an ‘equivalent’ resistor to represent a physical resistor which would absorb the same radiated power loss. This equivalent resistor is called the radiating resistance of the circuit. The radiating resistance of an antenna should not be confused with its input impedance. The input impedance is the value used when considering the connection of an antenna to a transmission line with a specified characteristic impedance. Antennas are bi-directional and it is not uncommon to use the same antenna for transmitting and receiving signals. Example 1.3 A transmitter with an output resistance of 72 W and an r.m.s. output of 100 V is connected via a matched line to an antenna whose input resistance is 72 W. Its radiation resistance is also 72 W. Assuming that the antenna is 100% efficient at the operating frequency, how much power will be transmitted into free space? 13 If you have any doubts about the system being bi-directional, you should visit a lighthouse which uses a similar reflector and lens system. Curtains must be drawn around the system during daylight hours because sunlight acting on the system has been known to produce such high light and heat intensities that insulation melt- down and fires have been caused. 16 Basic features of radio communication systems Given: Transmitter output = 100 V, transmitter output impedance = 72 Ω, antenna input impedance = 72 Ω, radiation resistance = 72 Ω, antenna efficiency = 100%. Required: Power radiated into free space. Solution. The antenna has an input impedance Z in = 72 Ω and provides a matched termi- nation to the 72 Ω line. The r.f. generator then ‘sees’ an impedance of 72 Ω, so the r.m.s. voltage applied to the line will be 100/2 = 50 V. The amount of power radiated is calcu- lated using radiated power = where R = 72 Ω is the radiation resistance. The radiated power is therefore 34.7 W. Notice that, because in this case R = Z in, maximum power is radiated into free space. 1.5.3 The half-wave dipole antenna Most antennas can be analysed by considering them to be transmission lines whose config- urations and physical dimensions have been altered to present easy energy transfer from transmission line to free space. In order to do this effectively, most antennas have physical sizes comparable to their operational wavelengths. Figure 1.12(a) shows a two wire transmission line, open-circuited at one end and driven by a sinusoidal r.f. generator. Electromagnetic waves will propagate along the line until it reaches the open-circuit end of the line. At the open-circuit end of the line, the wave will be reflected and travel back towards the sending end. The forward wave and the reflected wave then combine to form a voltage standing wave pattern on the line. The voltage is a maximum at the open end. At a distance of one quarter wavelength from Fig. 1.12 (a) Voltage standing-wave pattern on an open-circuited transmission line; (b) open-circuited line forming a Antennas and aerials 17 Fig. 1.13 Polar pattern of a half-wave dipole the end, the voltage standing wave is at a minimum because the sending wave and the reflected wave oppose each other. Suppose now that the wires are folded out from the λ/4 points, as in Figure 1.12(b). The resulting arrangement is called a half-wave dipole antenna. Earlier we said that the electromagnetic fields around the parallel conductors overlap and cancel outside the line. However, the electromagnetic fields along the two (λ/4) arms of the dipole are now no longer parallel. Hence there is no cancellation of the fields. In fact, the two arms of the dipole now act in series and are additive. They therefore reinforce each other. Near to the dipole the distribution of fields is complicated but at a distance of more than a few wavelengths electric and magnetic fields emerge in phase and at right- angles to each other which propagate as an electromagnetic wave. Besides being an effective radiator, the dipole antenna is widely used as a VHF and TV receiving antenna. It has a polar diagram which resembles a figure of eight (see Figure 1.13). Maximum sensitivity occurs for a signal arriving broadside on to the antenna. In this direction the ‘gain’ of a dipole is 1.5 times that of an isotropic antenna. An isotropic antenna is a theoretical antenna that radiates or receives signals uniformly in all directions. The gain is a minimum for signals arriving in the ‘end-fire’ direction. Gain decreases by 3 dB from its maximum value when the received signal is ±39° off the broadside direc- tion. The maximum gain is therefore 1.5 and the half-power beam-width is 78°. The input impedance of a half-wave dipole antenna is about 72 Ω. It turns out that the input imped- ance and the radiation resistance of a dipole antenna are about the same. 1.5.4 Folded dipole antenna The folded dipole (Figure 1.14) is a modified form of the dipole antenna. The antenna is often used for VHF FM receivers. The impedance of a folded λ/2 dipole is approximately 292 W. This higher input impedance is advantageous for two main reasons: 18 Basic features of radio communication systems Fig. 1.14 Folded dipole antenna • it allows easy connection to 300 W balanced lines. • its higher impedance makes it more compatible for use in directive aerials (particularly Yagi arrays) which will be described in Section 1.6. 1.5.5 The monopole or vertical rod antenna The monopole or vertical rod antenna (Figure 1.15) is basically a coaxial cable14 whose outer conductor has been removed and connected to earth. It is usually about λ/4 long except in cases where space restrictions or other electrical factors restrict its length. At high frequencies, the required λ/4 length is short and the antenna can be made self- supporting by the use of hollow metal tubing. At low frequencies where a greater length is required, the antenna is often supported by poles. Fig. 1.15 Rod or monopole antenna This antenna is favoured for use in low frequency transmitting stations, in portable radio receivers, in mobile radio-telephones, and for use on motor vehicles because it has a circu- lar polar receiving pattern, i.e. it transmits and receives signals equally well in all directions around its circumference. This is particularly important in mobile radio-phones and in motor vehicles because a motor vehicle may be moving in any direction with respect to a transmitting station. To minimise interference from the engine of the vehicle and for 14 A typical example of a coaxial cable is the TV lead which connects your television set to the antenna. Antennas and aerials 19 maximum receiving height, rod aerials are frequently mounted on the roofs of vehicles. These aerials are also often mounted at an angle of about 45° to the horizon to enable them to be receptive to both horizontal and vertical polarisation transmissions. 1.5.6 Single loop antennas Another type of antenna which is frequently used for TV reception is the single loop antenna shown in Figure 1.16. This loop antenna usually has an electrical length equal to approximately λ/2 at its operating frequency. It is popular with TV manufacturers because it is comparatively cheap and easy to manufacture. The antenna’s input impedance is approximately 292 Ω and it is easily coupled to 300 Ω balanced transmission lines. The antenna is directive and has to be positioned for maximum signal pick-up. Fig. 1.16 Single loop antenna 1.5.7 Multi-loop antennas At low frequencies, particularly at frequencies in the medium wave band where wave- lengths are long, single loop λ/2 length antennas are not practical; multi-loop antennas (Figure 1.17) are used instead. The multi-loop antenna can be reduced even further in size if a ferrite rod is inserted within the loop. The open-circuit voltage induced in multiple loop antennas can be calculated by making use of Faraday’s Law of Electromagnetic Induction which states that the voltage induced in a coil of n turns is proportional to the rate of change of magnetic flux linkage. For simplicity in derivation, it will be assumed that the incident radiation is propagating along the axis of the coil (see Figure 1.18). Fig. 1.17 Multi-loop antenna 20 Basic features of radio communication systems Fig. 1.18 Multi-looped antenna aligned for maximum flux linkage Expressing Faraday’s Law mathematically, e=n (1.10) e = open-circuit voltage in volts n = number of turns on coil dφ/dt = rate of change of magnetic flux linkage (φ = webers and t = seconds) Some fundamental magnetic relations are also required. These include: total flux φ = flux density (B) per unit area × area (A) φ webers = Btesla × Asquare metres (1.11) By definition flux density in air cored coil ( Btesla ) is given by free-space permeability (µ0) × magnetic field strength (H) B(tesla) = µ 0 (henry metre) × H(ampere metre) (1.12) Suppose that the incident wave has a magnetic field strength H = H max sin ωt (1.13) where ω is the angular frequency of the r.f. signal. Then substituting Equations 1.12 and 1.13 in Equation 1.11 yields φ = BA = µ 0 Hmax sin ωt × A (1.14) Taking the rate-of-change15 in Equation 1.14, then the induced voltage is = nωµ 0 AHmax cos ωt (1.15) 15 If you do not know how to differentiate to get the rate of change of a value, then please refer to a maths Antennas and aerials 21 For a coil with a ferrite core, the flux density is increased by the relative effective perme- ability (µr), giving e = nωµ 0 µ r AHmax cos ωt (1.16) You will see that the ferrite core has increased the effective area of the coil by a factor µr. Ferrite cores with effective relative permeabilities of 100–300 are readily available but even with these values, the effective area of the aerial is relatively small when compared with a λ/2 aerial length. The ferrite rod aerial is therefore very inefficient when compared to an outdoor aerial but it is popular because of its convenient size and portability. At medium wave frequencies, the inherent poor signal pick-up is acceptable because broad- cast stations radiate large signals. In the foregoing derivation, it has been assumed that the magnetic field has been cutting the coil along its axis. Occasions arise when the incident magnetic field arrives at an angle a with respect to the axis of the coil. This is shown in Figure 1.19. In this case the effec- tive core area is reduced by cos a, and the induced voltage becomes e = nωµ 0 AHmax cos ωt cos α (1.17) This expression shows that the induced open-circuit voltage, e, is dependent on the axial direction of the aerial coil with respect to the direction of the propagation. It is maximum when cos a = 1, i.e. a = 0°, and minimum when cos a = 0, i.e. a = 90°. This explains why it is necessary to position a loop aerial to receive maximum signal from a particular broad- casting station and this is done in a portable radio receiver by orienting its direction. The above reasons apply equally well to ferrite rod aerials and for these cases we have an induced voltage e = nωµ r µ 0 AHmax cos ωt cos α (1.18) If the magnetic field strength is given as an r.m.s. value (Hrms), then the r.m.s. value of the induced voltage is erms = nωµ r µ 0 AHrms cos α (1.19) Finally, ferrite aerials are seldom used at the higher frequencies because ferrite can be extremely lossy above 10 MHz. Fig. 1.19 H field arriving at an angle α 22 Basic features of radio communication systems Example 1.4 A coil of 105 turns is wound on a ferrite rod with an effective cross-sectional area of 8 × 10–5 m2. The relative permeability of the ferrite is 230 and the permeability of air is 4π × 10–7 henry/m. The r.m.s. field strength is 10 µA/m. If the magnetic field is incident along the axis of the coil and the frequency of operation is 1 MHz, what is the r.m.s. open-circuit voltage induced in the coil? Given: No. of coil turns = 105, effective cross-sectional area of ferrite rod = 8 × 10–5 m2, relative permeability (µr) = 230, permeability of air (µ0) = 4π × 10–7 Henry/metre, r.m.s. field strength = 10 µA/m, frequency = 1 MHz. Required: r.m.s. open-circuit voltage induced in coil. Solution. Using Equation 1.19 erms = nωµ r µ 0 AHrms cos α = 105 × 2π × 1 × 10 6 × 230 × 4π × 10 −7 × 10 × 10 −6 × 8 × 10 −5 × cos 0° = 152.5 µV Broadcasting authorities tend to quote electric field strengths rather than magnetic field strengths for their radiated signals. This creates no problems because the two are related by the wave impedance formula given earlier as Equation 1.8. This is repeated electric field strength ( E ) = 377 Ω magnetic field strength ( H ) Example 1.5 A coil of 100 turns is wound on a ferrite rod with an effective cross-sectional area of 8 × 10–5 m2 . The relative permeability of the ferrite is 200 and the permeability of air is 4π × 10–7 henry/m. The magnetic field is incident at an angle of 60° to the axis of the coil and the frequency of operation is 1 MHz. If the electric field strength is 100 µV/m, what is the r.m.s. open-circuit voltage induced in the coil? Given: No. of coil turns = 105, effective cross-sectional area of ferrite rod = 8 × 10–5 m2, relative permeability (µr) = 200, permeability, of air (µ0) = 4π × 10−7 henry/metre, incidence of magnetic field = 60°, frequency = 1 MHz, electric field strength = 100 Required: Open-circuit voltage (erms). Solution. Substituting Equation 1.8 in Equation 1.19 yields erms = nωµ r µ 0 A cos α 100 × 10 −6 = 100 × 2π × 1 × 10 6 × 200 × 4π × 10 −7 × 8 × 10 −5 × × cos 60° = 1.68 µV Antenna arrays 23 1.6 Antenna arrays 1.6.1 Introduction Antenna arrays are used to shape and concentrate energy in required patterns. One of the more common domestic arrays is the Yagi-Uda array used for the reception of television 1.6.2 Yagi-Uda array The Yagi-Uda aerial array shown in Figure 1.20 is one of the most commonly used antenna arrays. It is used extensively for the reception of TV signals and can be seen on the roofs of most houses. The Yagi array is an antenna system designed with very similar principles to the car headlamp system described in Section 1.5.1. Its main elements are a folded dipole, a reflector, and directivity elements which serve as ‘electrical lenses’ to concentrate the signal into a more clearly defined beam. The number of directors per array varies according to the gain required from the aerial. The length of directors and the spacing between them are also dependent on the number of elements used in the array. In general, gain increases with the number of directors, but greater gain needs more careful alignment with the transmitting station and requires that the antenna be more sturdily mounted otherwise its pointing direc- tion will waver in high winds which can cause fluctuations in the received signal strength. The Yagi array is usually designed to be connected to a 75 W transmission line.16 Yagi Fig. 1.20 Yagi-Uda array: (a) physical arrangement;(b) radiation pattern 16 Earlier on, we said that the impedance of a folded dipole aerial was 292 W, yet now we say that this antenna is designed to operate with a 75 W system. This apparent discrepancy arises because the use of reflector and direc- tors loads the folded dipole and causes its impedance to fall. Judicious director spacing is then used to set the array to the required impedance. 24 Basic features of radio communication systems arrays suitable for operation over the entire TV band can be obtained commercially, but these broadband arrays are usually designed to ‘trade off’ bandwidth against aerial gain. Broadband Yagi arrays are extremely useful for mobile reception where minimum space and convenience are of importance. (You often see them on top of mobile caravans.) Domestic Yagi arrays are usually designed to provide greater gain but with a more restricted operational frequency band. The latter is not a disadvantage because TV stations operating from a common transmitting site confine their broadcasts to well defined frequency bands. The common practice for domestic Yagi arrays17 is to use three or more designs (scaled in size) to provide reception for the complete TV band. Typical values for Yagi arrays operating in the TV band are shown in Table 1.1. These figures have been taken from a well known catalogue but some of the terms need expla- Table 1.1 Typical values for Yagi arrays operating in the TV band No. of elements Forward gain Front/back ratio Acceptance angle (±0.5 dB) (± 2 dB) (±3°) • ‘Number of elements’ means the total number of directors, folded dipoles and reflectors used in the array. For example, if the number of elements in an array is 10, the array includes eight directors, one folded dipole and one reflector. • ‘Forward gain’ is the maximum ‘gain’ which the antenna can provide with respect to an isotropic aerial. A maximum aerial gain of 10 dB means that the antenna will provide 10 times the ‘gain’ you would get from an isotropic aerial when the array is pointed in its maximum gain direction. • ‘Front to back ratio’ is the difference in gain between the direction of maximum antenna gain and the minimum direction of gain which is usually in the opposite direction. This ratio is important because it provides a measure of how the array behaves towards inter- fering signals arriving from different directions. It is particularly useful in confined areas such as cities where interfering signals ‘bounce’ off high buildings and interfere with a strong desired signal. In such cases, it is often better to select an antenna with a large front to back ratio to provide rejection to the interfering signal than trying to get maxi- mum antenna gain. • ‘Acceptance angle’ is the beamwidth angle in degrees where antenna gain remains within 3 dB of its stated maximum gain. An acceptance angle of 20° and a maximum array gain of 10 dB means that for any signal arriving within ±10° of the maximum gain direction the antenna will provide at least (10 – 3) dB, i.e. 7 dB of gain. However, you should be aware that the acceptance angle itself is not accurate and that it can vary by ±3° as well. 17 There is a class of Yagi arrays known as Log Periodic Yagis. These have greater bandwidths because the directors are spaced differently. They do cover the entire TV bands but their gain is a compromise between frequency bandwidth and gain. Antenna distribution systems 25 The values given in the table are representative of the middle range of commercially available Yagi arrays. The figures quoted above have been measured by manufacturers under ideal laboratory conditions and proper installation is essential if the specification is to be achieved in practice. 1.7 Antenna distribution systems Occasions often arise where it is desired to have one antenna supply signal to several tele- vision and radio receivers. A typical example is that of an apartment block, where a single aerial on the roof supplies signals to all the apartments. Another possible use for such a system is in your own home where you would like to distribute signals to all rooms from a single external aerial. In such cases, and for maximum efficiency, an aerial distribution system is used. There are many ways of designing such a system but before discussing them, it is best to understand some of the terms used. 1.7.1 Balanced and unbalanced systems Examples of balanced and unbalanced aerials and distribution lines are shown in Figures 1.21 and 1.22. You should refer to these figures while you are reading the descriptions given below. A balanced antenna (Figure 1.21(a) and (b)) is an aerial which has neither conductor connected directly to earth; it is balanced because the impedance between earth and each conductor is the same. A folded dipole is a typical example of a balanced antenna because the impedance from each end of the antenna to earth is equal and balanced. An unbalanced Fig. 1.21 Balanced antenna system and (a) balanced distribution system; (b) unbalanced distribution system 26 Basic features of radio communication systems Fig. 1.22 Unbalanced antenna system and (a) unbalanced distribution system; (b) balanced distribution system antenna (Figure 1.22(a) and (b)) is an aerial which has one of its conductors connected directly to earth. The impedance between earth and each conductor is not the same. A monopole aerial is a typical example of an unbalanced aerial because its other end (see Figure 1.15) is connected to earth. A balanced line (Figure 1.21(a) and (b)) is a transmission line where the impedance between earth and each conductor is identical. A twin pair cable is an example of a balanced line because the impedance between earth and each conductor is the same. An unbalanced line (Figures 1.22(a), 1.22(b) is a transmission line where the impedance between earth and each conductor is not equal. A coaxial cable is an example of an unbal- anced line because the impedance between earth and the outer shield is different to the impedance between earth and the inner conductor. The key to the connections in Figures 1.21 and 1.22 is the balanced/unbalanced trans- former. These transformers are carefully wound to produce maximum energy transfer by magnetic coupling. Coil windings are designed to have minimum self-capacitance, mini- mum inter-winding capacitance and minimum capacity coupling between each winding and earth. No direct connection is used between input and output circuits. The above conditions are necessary, otherwise balanced circuits will become unbalanced when parts of the circuit are connected together. The balanced/unbalanced transformer is bi-direc- tional; it can be used to pass energy in either direction. As the operational frequencies become higher and higher (above 2 GHz), it becomes increasingly difficult to make such a good transformer and a transformer is simply not used and antennas and transmission lines are connected directly. In such cases, the systems resolve to either an unbalanced antenna and distribution system or a balanced antenna and distribution system. The unbalanced system is almost always used because of convenience and costs. Antenna distribution systems 27 1.7.2 Multi-point antenna distribution systems In the design of antenna distribution systems, transmission lines connecting signal distribution points must function efficiently; they must carry signal with minimum loss, minimum inter- ference and minimum reflections. Minimum loss cables are made by using good conductivity materials such as copper conductors and low loss insulation materials. Minimum interference is obtained by using coaxial cables whose outer conductor shields out interference signals. Reflections in the system are minimised by proper termination of the cables. For proper termi- nation and no reflections in the system, two conditions must be fulfilled: • the antenna and cable must be terminated in its characteristic impedance Z 0; • the source impedance (Z s) feeding each receiver must be matched to the input imped- ance of the receiver (Z in), i.e. Z s = Z in, otherwise there will be signal reflections and minimum cable transmission loss will not be obtained. In Figure 1.23, an aerial of characteristic impedance (Z 0) is used to feed a transmission (TX) line with a characteristic impedance Z 0. The output of the line is fed to a number (n) of receivers, each of which is assumed to have an input impedance (Z in) equal to Z 0. Resis- tors R represent the matching network resistors which must be evaluated to ensure prop- erly terminated conditions. For the system to be properly terminated, it is essential that the aerial and cable system be terminated with Z 0, i.e. the impedance to the right of the plane ‘AE’ must present an impedance Z 0 to the antenna and cable system. It is also essential that each receiver be energised from a source impedance (Z s) matched to its own input impedance (Z in), i.e. Z s = Z in. For ease of analysis we will assume the practical case, Z s = Z in = Z 0. Now for the transmission line in Figure 1.23 to be properly terminated: R + [R + Z 0]/n = Z 0 Multiplying both sides by n: nZ 0 = nR + R + Z 0 Collecting and transposing terms gives: (n – 1) R = ——— Z 0 (1.20) (n + 1) Fig. 1.23 Aerial distribution system for n receivers, each with an input impedance of Zin 28 Basic features of radio communication systems This equation is all we need to calculate the value of the matching resistors in Figure Example 1.6 A 75 W aerial system is used to supply signals to two receivers. Each receiver has an input impedance of 75 W. What is the required value of the matching resistor? Given: 75 W aerial system, input impedance of each receiver = 75 Ω, no. of receivers = 2. Required: Value of matching resistor. Solution. Using Equation 1.20 with n = 2, we obtain (n – 1) (2 – 1) R = ——— Z 0 = ——— 75 = 25 W (n + 1) (2 + 1) Example 1.7 A 50 W aerial receiving system is to be used under matched conditions to supply signal to four receivers, each of input impedance 50 W. If the configuration shown in Figure 1.23 is used, calculate the value of the resistor, R, which must be used to provide matching condi- Given: 50 Ω aerial system, input impedance of each receiver = 50 Ω, no. of receivers = 4. Required: Value of matching resistor. Solution. From Equation 1.20 (n – 1) (4 – 1) R = ——— Z 0 = ——— 50 = 30 W (n + 1) (4 + 1) From the answers above, it would appear that an aerial system can be matched to any number of receivers. This is true only within limits because the signal level supplied to individual receivers decreases with the number of distribution points. With large numbers of receivers, network losses become prohibitive. Transmission losses associated with the matching network of Figure 1.23 can be calculated by reference to Figure 1.24. The network has been re-drawn for easier derivation of circuit losses but Z 0, R and n still retain their original definitions. Fig. 1.24 Calculating the signal loss in an antenna distribution system Antenna distribution systems 29 In Figure 1.24 Voc = open-circuit source voltage from the aerial Vce = terminated voltage at an intermediate point in the network Vout = terminated voltage at the input to a receiver By inspection ⎧ R + Z0 ⎫ ⎨ ⎬ Vout = Vce and Vce = ⎩ n ⎭ Voc R + Z0 ⎧ R + Z0 ⎫ + + ⎨ ⎬ R Z0 ⎩ n ⎭ Z0 R + Z0 Z0 Vout = × Voc = Voc R + Z0 (n + 1)( R + Z0 ) (n + 1)( R + Z0 ) Using Equation 1.20 and substituting R = [(n – 1)/(n + 1)]Z 0 in the above equation Z0 V Vout = Voc = oc ⎡ (n − 1) ⎤ 2n (n + 1)⎢ Z0 + Z0 ⎥ ⎣ (n + 1) ⎦ Transposing, we find that Vout 1 voltage transmission loss = = (1.21) Voc 2n voltage transmission loss = 20 log ⎡ ⎤dB18 ⎢ 2n ⎥ ⎣ ⎦ Example 1.8 A broadcast signal induces an open-circuit voltage of 100 µV into a rod aerial. The aerial system has a characteristic impedance of 50 Ω and it is used to supply signal to three iden- tical receivers each of which has an input impedance of 50 Ω. If the matching network type shown in Figure 1.23 is used, calculate (a) the value of the resistance (R) required for the matching network and (b) the terminated voltage appearing across the input terminals of the receiver. 18 dB is short for decibel. The Bel is a unit named after Graham Bell, the inventor of the telephone. 1 Bel = log10 [power 1(P1)/power 2(P2)]. In practice the unit Bel is inconveniently large and another unit called the deci- bel is used. This unit is 1/10 of a Bel. Hence 1 Bel = 10 dB or dB = 10 log10 [P1 /P2] = 10 log10 [(V12/R)/(V22/R)] = 20 log10 [V1/V2] 30 Basic features of radio communication systems Given: 50 Ω aerial system, input impedance of each receiver = 50 Ω, no. of receivers = 3, open-circuit voltage in aerial = 100 µV. Required: (a) Value of matching resistor, (b) terminated voltage at receiver input termi- (a) For the matching network of Figure 1.23 (n − 1) (3 − 1) R= Z0 = × 50 = 25Ω (n + 1) (3 + 1) (b) Using Equation 1.20 Vreceiver = Vantenna = × 100 µV = 16.67 µV 2n 6 1.7.3 Other aerial distribution systems The matching network shown in Figure 1.23 is only one type of matching network. Figure 1.25 shows a commercially available matching network for two outlets. This network is sometimes called a two way splitter because it splits the signal from a single input port into two output ports. The circuit has been designed for low insertion loss and it does this by trading off proper matching against insertion loss. Fig. 1.25 Two way splitter Example 1.9 Figure 1.25 shows a commercially available 75 Ω matching network. Calculate: (a) the ratio Vout/Voc when all ports are each terminated with 75 Ω, (b) the input impedance to the matching network when the output ports are each terminated with 75 Ω and (c) the source impedance to either receiver when the remaining ports are each terminated in 75 Ω. Given: 75 Ω network splitter of Figure 1.25 with 75 Ω terminations. Required: (a) Ratio Vout/Voc, (b) input impedance of matching network, (c) source impedance to either receiver. Solution. By inspection: 75 (43 + 75)/2 (a) Vout = ———— × ——————— × Voc = 0.28 43 + 75 (43 + 75)/2 + 75 Antenna distribution systems 31 (b) input impedance to the network = (43 + 75)/2 = 59 W (43 + 75)(75) (c) receiver source impedance = 43 + ——————— = 89 W (43 + 75) + (75) From the answers to Example 1.9, it can be seen that the insertion loss is slightly reduced but this has been carried out at the expense of system match. The manufacturer is fully aware of this but relies on the fact that the reflected signal will be weak and that it will not seriously affect signal quality. The manufacturer also hopes that the cable system will be correctly matched by the antenna and that any reflections set up at the receiver end will be absorbed by the hopefully matched antenna termination to the cable system. This design is popular because the installation cost of an additional resistor is saved by the manufac- 1.7.4 Amplified antenna distribution systems Amplified aerial distribution systems are aerial distribution systems which incorporate amplifiers to compensate for signal transmission, distribution and matching losses. Two systems will be discussed here. The first concerns a relatively simple distribution system where indoor amplifiers are used. The second system deals with a more elaborate system using amplifiers mounted on the aerial (masthead amplifiers) to compensate for distribu- tion and matching losses. 1.7.5 Amplified aerial distribution systems using amplifiers The block diagram of an amplified aerial distribution system using an amplifier is shown in Figure 1.26. This system is often used in domestic environments. Outdoor aerials provide the incoming signals, UHF for TV and/or VHF for FM-radio to the input of an amplifier. The gain of this amplifier is nominally greater than 10 dB but this varies accord- ing to the particular amplifier used. The amplifier is usually placed on the antenna mast- head or near the aerial down-lead cables and a power supply point in the attic. Fig. 1.26 Antenna amplifier distribution network 32 Basic features of radio communication systems Output signals from the amplifier are fed into matching networks for distribution to individual terminals. To save cabling costs, both UHF and VHF signals are often carried on the same cables. Filters (a high pass filter for UHF and a low pass filter for VHF) are installed at individual terminals to feed the signals to their designated terminals. The main advantage of such a system is that it is relatively easy to install especially if wiring for the distribution already exists. It also compensates for signal loss in the distrib- ution network. The amplifier casing is relatively cheap when the amplifier is used indoors as it does not have to be protected from extreme weather conditions. The main disadvan- tage of indoor mounting is that signals are attenuated by the aerial down-lead cables before amplification. This signal loss decreases the available signal before amplification and therefore a poorer signal-to-noise ratio is available to the distribution points than if the amplifier was to be mounted on the masthead. 1.8 Radio receivers 1.8.1 Aims The aims of this section are to introduce you to: • the tuned radio frequency receiver • the superhet receiver • the double superhet receiver • selectivity requirements in receivers • sensitivity requirements in receivers • concepts of signal-to-noise and sinad ratios • noise figures of receivers 1.8.2 Objectives After reading this section you should be able to understand: • the basic principles of tuned radio frequency receivers • the basic principles of superhet receivers • the basic principles of satellite receivers • the concepts of selectivity • the concepts of sensitivity • the concepts of signal-to-noise and sinad ratios • the concepts of noise figures 1.8.3 Introduction Radio receivers are important because they provide a valuable link in communications and entertainment. Early receivers were insensitive, inefficient, cumbersome, and required large power supplies. Modern designs using as little as one integrated circuit have overcome most of these disadvantages and relatively inexpensive receivers are readily Radio receiver properties 33 Fig. 1.27 Spacing of broadcast stations in the medium wave band 1.8.4 Fundamental radio receiver requirements In the AM medium wave band, broadcasting stations transmit their signals centred on assigned carrier frequencies. These carrier frequencies are spaced 9 kHz apart from each other as in Figure 1.27 and range from 522 kHz to 1620 kHz. The information bandwidth allocated for each AM transmission is 9 kHz. This means that modulation frequencies greater than 4.5 kHz are not normally used. To receive information from a broadcast signal, an AM broadcast receiver must be tuned to the correct carrier frequency, have a bandwidth that will pass the required modulated signal, and be capable of extracting infor- mation from the required radio signal to operate desired output devices such as loud- speakers and earphones. Discussions that follow pertain mainly to receivers operating in this band. This is not a limitation because many of the principles involved apply equally well to other frequency bands. When the need arises, specific principles applying to a particular frequency band will be mentioned but these occasions will be clearly indicated. 1.9 Radio receiver properties A radio receiver has three main sections (see Figure 1.28). • A radio frequency section to select and if necessary to amplify a desired radio frequency signal to an output level sufficient to operate a demodulator. • A demodulator section to demodulate the required radio signal and extract its modu- lated information. • A post-demodulation section to amplify demodulated signals to the required level to operate output devices such as loudspeakers, earphones and/or TV screens. Fig. 1.28 Three main sections of a radio receiver 34 Basic features of radio communication systems 1.9.1 Radio frequency section A radio frequency section is designed to have the following properties. Receiver selectivity is a measure of the ability of a radio receiver to select the desired transmitted signal from other broadcast signals. An ideal selectivity response curve for an AM broadcast receiver centred on a desired carrier frequency ( f 0) is shown in Figure 1.29. Two main points should be noted about the ideal selectivity response curve. First, it should have a wide enough passband (9 kHz approx.) to pass the entire frequency spectrum of the desired broadcast signal. Second, the passband should present equal transmission charac- teristics to all frequencies of the desired broadcast signal. In addition, the bandwidth should be no wider than that required for the desired signal because any additional band- width will allow extraneous signals and noise from adjacent channels to impinge on the receiver. Notice that the skirts of the ideal selectivity curve are vertical, so that the attenu- ation of any signal outside the passband is infinitely high. Fig. 1.29 Ideal selectivity curve for an AM medium wave broadcast receiver In practice, costs and stability constraints prevent the ideal selectivity response curve from ever being attained and it is more rewarding to examine what is achieved by commer- cial receivers. An overall receiver selectivity response curve for a typical domestic transistor receiver for the reception of AM broadcast signals is shown in Figure 1.30. In the table supplied with Figure 1.30, you should note that the selectivity curve is not symmetrical about its centre frequency. This is true of most tuned circuits because the effective working quality factor (Qw) of components, particularly inductors, varies with frequency. Note also that the 3 dB bandwidth is only 3.28 kHz and that the 6 dB bandwidth points are approximately 4.82 kHz apart. The 60 dB points are 63.1 kHz apart. Consider the case of a carrier signal (f0) modulated with two inner sideband frequen- cies f1L, f1U (±1.64 kHz) and two outer sideband frequencies f2L, f2U (±2.4 kHz) away from the carrier. The frequency spectrum of this signal is shown in Figure 1.31(a). When Radio receiver properties 35 Fig. 1.30 Typical selectivity curve of a commercial AM six transistor receiver this frequency spectrum is passed through a receiver with the selectivity response shown in Figure 1.30, the inner sidebands f1L, f1U (±1.64 kHz) and the outer sidebands f2L, f2U (±2.4 kHz) will suffer attenuations of 3 dB and 6 dB approximately with respect to the carrier. (See the table in Figure 1.30.) The new spectrum of the signal is shown in Figure Comparison of Figures 1.31(a) and (b) shows clearly that amplitude distortion of the sidebands has occurred but what does this mean in practice? If the transmitted signal had been music, there would have been an amplitude reduction in high notes. If the transmit- ted signal had been speech, the speaker’s voice would sound less natural. Fig. 1.31(a) Transmitted spectrum Fig. 1.31(b) Distorted spectrum From the above discussion, it should be noted that for good quality reproduction the selectivity curve of a receiver should be wide enough to pass all modulation frequencies without discriminatory frequency attenuation. Adjacent channel selectivity A graphical comparison of the selectivity curves of Figures 1.29 and 1.30 is shown in Figure 1.32. From these curves, it can be seen that the practical selectivity curve does not provide complete rejection of signals to stations broadcasting on either side of the desired 36 Basic features of radio communication systems Fig. 1.32 A comparison between the ideal and practical selectivity curve response channel. The breakthrough of signal from adjacent channels into the desired channel is known as adjacent channel interference. Adjacent channel interference causes signals from adjacent channels to be heard in the desired channel. It is particularly bad when strong adjacent channel signals are present relative to the desired station. What does this mean in practice? It means that you will obtain interference from the unwanted station. In a broadcast receiver, you often hear signals from both channels simultaneously. Broadcasting authorities minimise adjacent channel interference by forbidding other transmitters situated near the desired station to broadcast on an adjacent channel. Stations geographically distant from the desired station are allowed to operate on adjacent channels because it is likely that their signals will have suffered considerable transmission loss by the time they impinge on the desired channel. The sensitivity of a radio receiver is a measure of the modulated signal input level which is required to produce a given output level. A receiver with good sensitivity requires a smaller input signal than a receiver with poor sensitivity to produce a given output level. The sensitivity of a small portable receiver (audio output rated at 250 mW) may be quoted as 200 µV/m. What this means is that a modulated AM carrier (modulated with a 400 Hz tone and with an AM modulation depth of 30%) will produce an audio output of 50 mW under its maximum gain conditions when the input signal is 200 mV/m. 1.9.2 Signal-to-noise ratios Any signal transmitted through a communications system suffers attenuation in the passive (non-amplifying) parts of the system. This is particularly true for radio signals propagating between transmitting and receiving aerials. Attenuation is compensated for by subsequent amplification, but amplifiers add their own inherent internally generated random noise to the signal. Noise levels must always be less than the required signal, otherwise the required signal will be lost in noise. Some means must be provided to Types of receivers 37 specify the level of the signal above noise. This means is called the Signal-to-Noise ratio. It is defined as: S signal power signal-to-noise ratio = — = —————— (1.23) N noise power Notice that S/N is specified as a ratio of power levels. An alternative way of specifying signal-to-noise ratios is to quote the ratio in decibels. This is defined by Equation 1.24: S ⎡ signal power ⎤ signal-to-noise ratio = (dB) = 10 log10 ⎢ ⎥ dB (1.24) N ⎣ noise power ⎦ A strong signal relative to the noise at the receiver input is essential for good reception. In practice, we require an S/N of 10–20 dB to distinguish speech, an S/N of 30 dB to hear speech clearly, and an S/N of 40 dB or better for good television pictures. Noise figure Certain amplifiers have more inherent electrical noise than others. Manufacturers usually produce a batch of transistors, then classify and name the transistors according to their inherent electrical noise levels. The inherent noise produced by a transistor is dependent on its general operating conditions, particularly frequency, temperature, voltage and oper- ating current, and these conditions must be specified when its noise level is measured. Engineers use the ratio term noise figure to specify noise levels in transistors. Noise figure is defined as [ ] noise figure (N.F.) = ——— at 290 K (1.25) If a transistor introduces no noise, then its S/N at both the input and output is the same, therefore from Equation 1.25, N.F. = 1 or in dB N.F. = 10 log 1 = 0 dB. Hence a ‘perfect’ or ‘noiseless’ amplifier has a noise figure of 0 dB. An imperfect amplifier has a noise figure greater than 0 dB. For example an amplifier with a noise figure of 3 dB (= 2 ratio) means that it is twice as bad as a perfect amplifier. 1.10 Types of receivers There are many types of radio receivers. These include: • tuned radio frequency receivers (TRF) • superheterodyne receivers (superhets) • double superheterodyne receivers (double superhets) 1.10.1 Tuned radio frequency receiver A tuned radio frequency receiver (Figure 1.33) has three main sections, a radio frequency amplifier section, a detector section, and an audio amplifier section. 38 Basic features of radio communication systems Fig. 1.33 Main sections of a tuned radio frequency receiver The radio frequency section consists of one or more r.f. amplifiers connected in cascade.19 For efficient operation, all tuned circuit amplifiers must be tuned to exactly the same broadcast frequency and to ensure that this is the case, all tuning adjusters are fixed on to a common tuning shaft. Tuning capacitors which are connected in this manner are said to be ‘ganged’ and two and three stage ganged tuning capacitors are common. The detector is usually a conventional AM diode type detector. This type of detector is usually a diode which detects the positive peaks of the modulated carrier and filters the r.f. out, so that the remaining signal is the inital low frequency modulation frequency. The audio section uses audio amplifiers which serve to amplify the signals to operate a loudspeaker. This section is similar to the amplifier in your home which is used for play- ing compact disks (CD) and cassettes. The main advantages of TRF receivers are that they are relatively simple, easy to construct, and require a minimum of components. A complete TRF receiver can be constructed using a single integrated circuit such as a ZN414 type chip. TRF receivers suffer from two main disadvantages, gain/bandwidth variations and poor selectivity. The inevitable change of gain and bandwidth as the receiver is tuned through its frequency range is due to changes in the selectivity circuits. Circuit instability can be a problem because it is relatively easy for any stray or leaked signal to be picked up by one of the many r.f. amplifiers in the receiver. R.F. signal can also be easily coupled from one r.f. stage to another through the common power supply. To minimise these risks, r.f. amplifiers are usually shielded and de-coupled from the common power supply. 1.10.2 Superheterodyne receiver Block diagram A block diagram of a superheterodyne (commonly called superhet) receiver is shown in Figure 1.34. This receiver features an r.f. section which selects the desired signal frequency ( frf). This signal is then mixed with a local carrier at frequency (fo) in a frequency changer to produce an intermediate frequency ( fif) which retains the modulated information initially 19 Here, cascade is meant to imply one amplifier following another amplifer and so on. Types of receivers 39 Fig. 1.34 Block diagram of a superhet radio receiver carried by frf. The intermediate frequency (fif) then undergoes intensive amplification (60–80 dB) in the intermediate frequency amplifiers to bring the signal up to a suitable level for detection and subsequent application to the post-detection (audio) amplifiers. Radio frequency amplifiers are sometimes included in the r.f. section in order to make the noise figure of the receiver as small as possible. Frequency changers have compara- tively larger noise figures (6–12 dB) than r.f. amplifiers. The frequency of the local oscillator ( fo) is always set so that its frequency differs from the desired frequency ( frf) by an amount equal to the intermediate frequency ( fif), i.e. fo – frf = fif (1.26) frf – fo = fif (1.27) Equation 1.26 is more usual for medium-wave receivers. Typical tuning ranges for a medium-wave receiver with fif = 465 kHz are 522–1620 kHz for frf and 987–2085 kHz for The main advantages of the superhet receiver are as follows. • Better selectivity because fixed bandpass filters with well defined cut-off frequency points can be used in the i.f. stages of a superhet. Filters and tuned circuits are also less complex because they need only operate at one frequency, namely the intermediate frequency. • In a superhet, tuning is relatively simple. A two ganged capacitor can be used to tune the r.f. and oscillator sections simultaneously to produce the intermediate frequency for the i.f. amplifiers. • R.F. circuit bandwidths are not critical because receiver selectivity is mainly determined by the i.f. amplifiers. The main disadvantages of superhets are as follows. • Image channel interference is caused by the local oscillator (fo) combining with an undesired frequency (fim) which is separated from the desired frequency (frf) by twice the i.f. frequency (fif). Expressed mathematically 40 Basic features of radio communication systems fim = frf ± 2fif (1.28) The term 2nd channel interference is another name for image channel interference. Image channel interference is more easily understood by substituting some arbi- trary values into Equations 1.26 and 1.27. For example, assume that the local oscil- lator of a superhet is set to 996 kHz and that its intermediate frequency amplifiers operate at 465 kHz. Then, either of two input frequencies, 996 – 465 = 531 kHz (Equation 1.26) or 996 + 465 = 1461 kHz (Equation 1.27), will mix with the local oscillator to produce a signal in the i.f. amplifiers. If the desired frequency is 531 kHz, then the undesired frequency of 1461 kHz is 2( fif) or 930 kHz away, i.e. it forms an image on the other side of the oscillator frequency. This condition is shown graphically in Figure 1.35. • There is the possibility that any strong signal or sub-harmonics of 465 kHz (fif) might impinge directly on the i.f. amplifiers and cause interference. • Any harmonic of the oscillator (fo) could mix with an unwanted signal to produce unwanted responses. For example 2 × 996(fo) kHz – 1527 kHz = 465 kHz The spurious responses stated above are minimised in superhets by using tuned circuits in the r.f. section of the receiver to select the desired signal and to reject the undesired ones. The local oscillator is also designed to be ‘harmonic free’. Fig. 1.35 Image response in superhet receivers 1.10.3 Double superheterodyne receivers A block diagram of a double conversion superhet used for receiving direct broadcast signals (DBS) from satellites is shown in Figure 1.36. Direct broadcasting satellites for the United Kingdom region transmit in the 11.6–12.4 GHz band. Each TV channel uses a 26 MHz bandwidth. The double superhet is basically a superhet receiver with two i.f. sections. The first i.f. section operates at a much higher i.f. frequency than the second i.f. section. This choice is deliberate because a higher 1st i.f. frequency gives better image channel rejection. You have already seen this in the calculations of p. 40. The 2nd i.f. section is made to operate at a lower frequency because it gives better adjacent channel selectivity. In this receiver, the input signal, f1, is selected, mixed with a local oscillator carrier, fx, and frequency translated to form the first i.f. frequency ( fif1). This signal is applied to the Summary 41 Fig. 1.36 Block diagram of a double conversion superhet receiver 1st i.f. amplifier section, then mixed with fo to produce a second intermediate frequency (fif2) and amplified prior to detection and low frequency amplification. In a typical direct broadcast satellite receiver, the first r.f. amplifier section operates in the band 11.6–12.4 GHz. The first local oscillator ( fx) is operated at a fixed frequency of 10.650 GHz. The resultant first i.f. frequency bandwidth range is 950 to 1750 MHz and is really the r.f. band translated to a lower frequency band. This i.f. is then amplified by the first set of 1st i.f. amplifiers. All the foregoing action takes place in a masthead unit which is mounted directly on the antenna. The total gain including r.f. amplification, frequency conversion and i.f. amplification is about 55 dB. This high order of gain is necessary to compensate for the losses which occur in the down-lead coaxial cable to the satellite receiver which is situated within the domestic environment. The satellite receiver treats the 1st i.f. frequency band (950–1750 MHz) as a tuning band and fo is varied to select the required TV channel which is amplified by the 2nd i.f. section before signal 1.11 Summary The main purpose of Chapter 1 has been to introduce you to the radio environment in your home. The knowledge you have gained will assist you in understanding basic radio prop- agation and reception principles. It will also help you to remedy some of the simpler radio and TV problems which you are likely to encounter in your home. In Sections 1.1–1.3, we started with the necessity for modulation and demodulation and you were introduced to the basic principles of modulation, demodulation and radio prop- agation. You should now understand the meaning of terms such as amplitude modulation (AM), frequency modulation (FM), phase modulation (PM) and digital modulation. In Section 1.4, you were introduced to radio propagation, wave polarisation, field strength and power density of radio waves. 42 Basic features of radio communication systems In Sections 1.5 and 1.6, you learned about the properties of several antennas. These included l/2 dipole, folded dipole, monopole, loop antennas and the Yagi-Uda array. Section 1.7 dealt with various antenna distributions and matching systems. In Section 1.8, you encountered some basic concepts concerning the reception of radio signals. You should now be able to carry out simple calculations with regard to selectivity, adjacent channel selectivity, sensitivity, S/N ratio and noise figure ratio as applied to radio Sections 1.9 and 1.10 described the main functions required in a radio receiver, and also the main advantages and disadvantages of three basic radio receiver types, namely the TRF, superhet and double superhet receivers. The first type is used in very simple receivers, the second type is used extensively in domestic receivers and the last type is used for direct broadcast reception from satellites. You have now been provided with an overview of a basic radio communication system. Having established this overview, we will now be in a position to deal with individual sub- systems and circuits in the next chapters. Transmission lines 2.1 Introduction At this stage, I would like to prepare you for the use of the software program called PUFF which accompanies this book. PUFF (Version 2.1) is very useful for matching circuits, and the design of couplers, filters, line transformers, amplifiers and oscillators. Figure 2.1 shows what you see when you first open the PUFF program. Figure 2.2 shows you how the program can be used in the design of a filter. In Figure 2.1 you can see for yourself that Fig. 2.1 PUFF 2.1 – blank screen (words in italics have been added for explanation) 44 Transmission lines Fig. 2.2 Bandpass filter design using PUFF to understand and use the program, you must be familiar with Smith charts (top right hand corner) and scattering or ‘s-parameters’ (top left hand corner), transmission lines and the methods of entering data (F3 box) into the program. Within limits, the layout window (F1 box) helps to layout your circuit for etching. 2.1.1 Aims We shall cover the basic principles of transmission lines in this part, and Smith charts and s-parameters in Part 3. We will then be in a position to save ourselves much work and avoid most of the tedious mathematical calculations involved with radio and microwave engi- The main aims of this chapter are: • to introduce you to various types of transmission lines; • to explain their characteristic impedances from physical parameters; • to provide and also to derive expressions for their characteristic impedances; • to explain their effects on signal transmission from physical and electrical parameters; • to explain and derive expressions for reflection coefficients; • to explain and derive expressions for standing wave ratios; • to explain and derive the propagation characteristics of transmission lines; • to provide an understanding of signal distortion, phase velocity and group delay; Transmission line basics 45 • to show how transmission lines can be used as inductors; • to show how transmission lines can be used as capacitors; • to show how transmission lines can be used as transformers. 2.1.2 Objectives This part is mainly devoted to transmission lines. Knowledge of transmission lines is necessary in order to understand how high frequency engineering signals can be efficiently moved from one location to another. For example, the antenna for your domestic TV receiver is usually mounted on the roof and it is therefore necessary to find some means of efficiently transferring the received signals into your house. In the commercial world, it is not unusual for a radio transmitter to be situated several hundred metres from a mast- mounted transmitting antenna. Here again, we must ensure that minimal loss occurs when the signal is transferred to the antenna for propagation. 2.2 Transmission line basics 2.2.1 Introduction to transmission lines In this discussion we shall start off using some basic terms which are easily understood with sound waves. We will then use these terms to show that these properties are also applicable to electrical transmission systems. Much of the explanation given in these sections will be based on examples using sinusoids because they are easier to understand. But this information applies equally well to digital waveforms because digital signals are composed of sinusoid components combined in a precise amplitude and phase manner. Therefore, it is vitally important that you do not form the mistaken idea that transmission line theory only applies to analogue waveforms. 2.2.2 General properties of transmission systems Transmission systems are used to transfer energy from one point to another. The energy transferred may be sound power or electrical power, or digital/ analogue/optical signals or any combination1 of the above. One easy way of refreshing your memory about signal transmission is to imagine that you are looking into a deep long straight tunnel with walls on either side of you. When you speak, you propagate sound energy along a transmission path down the length of the tunnel. Your voice is restricted to propagation along the length of the tunnel because walls on either side act as waveguides. Waves emerging directly from the sender are known as incident waves. As your vocal cords try to propagate incident waves along the tunnel, they encounter an opposition or impedance caused by the air mass in the tunnel. The impedance is determined by the physical characteristics of the tunnel such as its width and height and the manner in which 1 For example, the coaxial cable connecting the domestic satellite receiver to the low noise amplifier on the satellite dish often carries d.c. power up to the low noise amplifier, radio frequency signals down to the receiver, and in some cases even digital control signals for positioning the aerial. 46 Transmission lines it impedes air mass movement within the tunnel. This impedance is therefore called the characteristic impedance (Z 0) of the tunnel. Bends or rock protrusions along the tunnel walls cause a change in the effective dimen- sions of the tunnel. These discontinuities in effective dimensions can cause minor reflec- tions in the signal propagation path. They also affect the characteristic impedance of the transmission channel. You should note that the walls of the tunnel do not take part in the main propagation of sound waves. However, they do absorb some energy and therefore weaken or attenuate the propagated sound energy. Amplitude attenuation per unit length is usually represented by the symbol α. Moss, lichen and shrubs growing on the walls will tend to absorb high frequency sound better than low frequency sound, therefore your voice will also suffer frequency attenu- ation. Frequency attenuation is known as dispersion. There is also a speed or propagation velocity with which your voice will travel down the tunnel. This velocity is dependent on the material (air mixture of gases), its density and temperature within the tunnel. With sound waves, this velocity is about 331 metres per If the tunnel is infinitely long, your voice will propagate along the tunnel until it is totally attenuated or absorbed. If the tunnel is not infinitely long, your voice will be reflected when it reaches the end wall of the tunnel and it will return to you as an echo or reflected wave. The ratio reflected wave/incident wave is called the reflection coefficient. You can prevent this reflection if it were physically possible to put some good sound absorption material at the end of the tunnel which absorbs all the incident sound. In other words, you would be creating a matching termination or matched load impedance (ZL) which matches the propagation characteristics of an infinitely long tunnel in a tunnel of finite length. The ratio of the received sound relative to the incident sound is known as the transmission coefficient. A signal travelling from a point A to another point B takes time to reach point B. This time delay is known as propagation time delay for the signal to travel from point A to point B. In fact, any signal travelling over any distance undergoes a propagation time Time propagation delay can be specified in three main ways: (i) seconds, (ii) periodic time (T) and (iii) phase delay. The first way is obvious, one merely has to note the time in seconds which it has taken for a signal to travel a given distance. Periodic time (T) is an interval of time; it is equal to [1/(frequency in Hz)] seconds. For example, if a 1000 Hz sinusoid requires four periodic times (4T) to travel a certain distance, then the time delay is 4 × (1/1000) seconds or four milliseconds. Phase delay can be used to measure time because there are 2π radians in a period time (T). For the example of a 1000 Hz signal, a phase delay of (4 × 2π) radians is equivalent to four periodic times (T) or four millisec- onds. Phase delay per unit length is usually represented by the symbol (β). It is measured in radians per metre. Hence if we were to sum up propagation properties, there would be at least three prop- erties which are obvious: • attenuation of the signal as it travels along the line; • the time or phase delay as the signal travels along the line; • dispersion which is the different attenuation experienced by different frequencies as it travels along a line. Types of electrical transmission lines 47 Finally, if you walked along a tunnel which produces echoes, while a friend whistled at a constant amplitude and pitch, you would notice the reflected sound interfering with the incident sound. In some places, the whistle will sound louder (addition of incident and reflected signal); in other places the whistle will sound weaker (subtraction of incident and reflected signal). Provided your friend maintains the whistle at a constant amplitude and pitch, you will find that louder and weaker sounds always occur at the same locations in the tunnel. In other words, the pattern of louder and weaker sounds remains stationary and appears to be standing still. This change in sound intensity levels therefore produces a standing wave pattern along the length of the tunnel. The ratio of the maximum to mini- mum sound is known as the standing wave ratio (SWR). It will be shown later that the measurement of standing wave patterns is a very useful technique for describing the prop- erties of transmission line systems. In the above discussions, you have used knowledge gained from the university of life to understand the definitions of many transmission line terms. These definitions are not trivial because you will soon see that many of the above principles and terms also relate to electrical transmission lines. In fact, if you can spare the time, re-read the above paragraphs again just to ensure that you are fully cognisant of the terms shown in bold 2.3 Types of electrical transmission lines Many of the terms introduced in the last section also apply to electrical transmission lines. However, you should be aware of the great difference in the velocity of sound waves (331 ms –1) and the velocity of electrical waves (3 × 108 ms –1 in air). There is also a great differ- ence in frequency because audible sound waves are usually less than 20 kHz whereas radio frequencies are often in tens of GHz. For example, satellite broadcasting uses frequencies of about 10–12 GHz. Since wavelength = velocity/frequency, it follows that there will be a difference in wavelength and that in turn will affect the physical size of transmission lines. For example, the dimensions of a typical waveguide (Figure 2.3(a)) for use at frequencies between 10 GHz and 15 GHz are A = 19 mm, B = 9.5 mm, C = 21.6 mm, D = 12.1 mm. There are many types of transmission lines.2 These range from the two wire lines which you find in your home for table lamps, and three wire lines used for your electric kettle. Although these cables work efficiently at power frequencies (50~60 Hz), they become very inefficient at high frequencies because their inherent construction blocks high frequency signals and encourages radiation of energy. 2.3.1 Waveguides and coplanar waveguides Other methods must be used and one method that comes readily to mind is the tunnel or waveguide described in Section 2.2.2. This waveguide is shown in Figure 2.3(a). It works efficiently as a high frequency transmission line because of its low attenuation and radia- tion losses but it is expensive because of its metallic construction (usually copper). It is also relatively heavy and lacks flexibility in use because special arrangements must be 2 The term ‘transmission line’ is often abbreviated to ‘tx lines’. 48 Transmission lines Fig. 2.3 (a) Metallic waveguide; (b) coplanar waveguide used to bend a transmission path. One variant of the waveguide is known as the coplanar waveguide (Figure 2.3(b)). 2.3.2 Coaxial and strip lines Another way of carrying high frequency signals is to use a coaxial transmission line simi- lar to the one that connects your TV set to its antenna. The coaxial line is shown in Figure 2.4(a). This is merely a two wire line but the outer conductor forms a circular shield around the inner conductor to prevent radiation. One variation of the coaxial line appears as the strip line (Figure 2.4(b)). The strip line is similar to a ‘flattened’ coaxial line. It has the advantage that it can be easily constructed with integrated circuits. Fig. 2.4 (a) Coaxial cable; (b) strip line 2.3.3 Microstrip and slot lines The microstrip line (Figure 2.5(a)) is a variant of the stripline with part of the ‘shield’ removed. The slot line (Figure 2.5(b)) is also a useful line for h.f. transmission. Types of electrical transmission lines 49 Fig. 2.5 (a) Microstrip line; (b) slot line 2.3.4 Twin lines In Figure 2.6, we show a sketch of a twin line carefully spaced by a polyethylene dielec- tric. This is used at relatively low frequencies. This twin cable is designed to have a characteristic impedance (Z 0) of approximately 300 W and it is frequently used as a VHF cable or as a dipole antenna for FM radio receivers in the FM band. The parallel wire line arrangement of Figure 2.6 without a dielectric support can also be seen mounted on poles as overhead telephone lines, overhead power lines, and sometimes as lines connecting high power, low and medium frequency radio transmitters to their antennas. Fig. 2.6 Twin parallel wire VHF cable All seven transmission lines shown in Figures 2.3–2.6 have advantages and disadvan- tages. For minimum loss, you would use the waveguide, the coaxial line and the strip line in integrated circuits. However, the latter two lines present difficulties in connecting exter- nal components to the inner conductor. The coplanar waveguide is better in this respect and finds favour in monolithic microwave integrated circuits (MMIC) because it allows easy series and parallel connections to external electrical components. The microstrip line is also useful for making series connections but not parallel connections because the only way through to the ground plane is either through or around the edge of the substrate. This is particularly true when a short circuit is required between the upper conductor and the ground plane; holes have to be drilled through the substrate. Microstrip also suffers from radiation losses. Nevertheless, microstrip can be made easily and conveniently and it is therefore used extensively. 50 Transmission lines 2.3.5 Coupled lines Coupled lines are lines which are laid alongside each other in order to permit coupling between the two lines. One example of microstrip coupled lines is shown in the F1 layout box of Figure 2.2 where three sets of coupled lines are used to couple energy from input port 1 to output port 4. 2.4 Line characteristic impedances and physical parameters The characteristic impedance of transmission lines is calculated in two main ways: • from physical parameters and configuration; • from distributed electrical parameters of the line. Some relevant expressions for calculating the impedance of these lines from physical parameters are given in the following sections. 2.4.1 Coaxial line characteristic impedance (Z0) The expression for calculating the characteristic impedance of the coaxial transmission line shown in Figure 2.4(a) is: 138 D Z 0 = —— log10 — (2.1) e d d = outer diameter of the inner conductor D = inner diameter of the outer conductor e = dielectric constant of the space between inner and outer conductor (e = 1 for air) Example 2.1 You will often find two types of flexible coaxial cables: one with a characteristic imped- ance Z 0 of 50 W which is used mainly for r.f. instrumentation and the other has a charac- teristic impedance of 75 W used mainly for antennas. The inner diameter of the outer conductor is the same in both cables. How would you distinguish the impedance of the two cables using only your eye? Solution. In general, to save money, both cables are normally made with the same outer diameter. This is even more evident when the cables are terminated in a type of r.f. connec- tor known as BNC.3 Since these connectors have the same outer diameter, by using Equa- tion 2.1 you can deduce that for Z 0 = 75 W, the inner conductor will be smaller than that of the 50 W cable. In practice, you will be able to recognise this distinction quite easily. 3 BNC is an abbreviation for ‘baby N connector’. It is derived from an earlier, larger threaded connector, the Type N connector, named after Paul Neill, a Bell Laboratories engineer. BNC uses a bayonet type fixing. There is also a BNC type connector which uses a thread type fixing; it is called a TNC type connector. Line characteristic impedances and physical parameters 51 2.4.2 Twin parallel wire characteristic impedance (Z0) The expression for calculating the characteristic impedance of the type of parallel trans- mission line shown in Figure 2.6 is: 276 2D Z 0 ≈ —— log10 —— (2.2) e d d = outer diameter of one of the identical conductors D = distance between the centres of the two conductors e = relative dielectric constant = 1 for air Example 2.2 The twin parallel transmission line shown in Figure 2.6 is separated by a distance (D) of 300 mm between the centre lines of the conductors. The diameter (d) of the identical conductors is 4 mm. What is the characteristic impedance (Z 0) of the line? Assume that the transmission line is suspended in free space, i.e. e = 1. Given: D = 300 mm, d = 4 mm, e = 1. Required: Z 0. Solution. Using Equation 2.2 276 2D 276 2 × 300 Z 0 ≈ —— log10 —— = —— log10 ———— ≈ 600 W 1 d 1 4 2.4.3 Microstrip line characteristic impedance (Z0) Before we start, it is best to identify some properties that are used in the calculations on microstrip. These are shown in Figure 2.7 where w = width of the microstrip, h = thick- ness of the substrate, t = thickness of the metallisation normally assumed to approach zero in these calculations, er = dielectric constant of the substrate. Note that there are two dielectric constants involved in the calculations, the relative bulk dielectric constant er and the effective dielectric constant ee. The effective dielectric is inevitable because some of the electric field passes directly from the bottom of the strip width to the ground plane whereas some of the electric field travels via air and the substrate to the ground plate. Fig. 2.7 (a) Microstrip line; (b) end view of microstrip line 52 Transmission lines There are many expressions for calculating microstrip properties4 but we will use two main methods. These are: • an analysis method when we know the width/height (w/h) ratio and the bulk dielectric constant (er) and want to find Z 0; • a synthesis method when we know the characteristic impedance Z 0 and the bulk dielec- tric constant (er) and want to find the w/h ratio and the effective dielectric constant (ee). Analysis formulae In the analysis case we know w/h and er and want to find Z 0. The expressions which follow are mainly due to H. Wheeler’s work.5 For narrow strips, i.e. w/h < 3.3 ⎧ ⎡ ⎤ 1 ⎛ ε − 1⎞ ⎛ π 1 ⎫ ⎪ ⎢ 4h h 2 4⎞⎪ + 16⎛ ⎞ + 2 ⎥ − ⎜ r Z0 = ⎨ ln ⎟⎜ ln + ln ⎟ ⎬ (2.3) 2(ε r + 1) ⎝ w⎠ ⎥ 2 ⎝ ε r + 1⎠ ⎝ 2 ε r π ⎠ ⎪ ⎪ ⎢w ⎩ ⎣ ⎦ ⎭ For wide strips, i.e. w/h > 3.3 119.9 ⎧ w ln 4 ln (επ 2 16) ⎛ ε r − 1⎞ Z0 = ⎨ + + ⎜ 2 ⎟ 2 ε r ⎪ 2h ⎩ π 2π ⎝ εr ⎠ ε + 1 ⎡ πε r + r ⎛w ⎞ ⎤⎫ ⎢ln 2 + ln⎝ 2 h + 0.94⎠ ⎥ ⎬ 2πε r ⎣ ⎦⎭ Synthesis formulae In the synthesis case we know Z 0 and er and want to find w/h and ee. For narrow strips, i.e. Z 0 > (44 – 2er) W w ⎛ exp H 1 ⎞ =⎜ − ⎟ (2.5) h ⎝ 8 4 exp H ⎠ Z0 2(ε r + 1) 1 ε r − 1 ⎛ π 1 4⎞ H= + ⎜ ln + ln ⎟ (2.6) 119.9 2 εr + 1 ⎝ 2 εr π ⎠ ε +1 ⎡ 1 εr − 1 ⎛ π 1 4⎞⎤ εe = r + ⎢1 − ⎜ ln + ln ⎟ ⎥ (2.7) 2 ⎢ ⎣ 2H εr + 1 ⎝ 2 εr π ⎠ ⎦⎥ Note: Equation 2.7 was derived under a slightly different changeover value of Z 0 > (63 – er) Ω. 4 In practice these are almost always calculated using CAD/CAE programmes. 5 Wheeler, H.A. Transmission lines properties of parallel wide strips separated by a dielectric sheet, IEEE Trans, MTT-13 No. 3, 1965. Line characteristic impedances and physical parameters 53 For wide strips, i.e. Z 0 < (44 – 2er)Ω w 2 ε −1 ⎡ 0.517 ⎤ = [( de − 1) − ln(2 de − 1)] + r ⎢ln ( de − 1) + 0.293 − ⎥ (2.8) h π πε r ⎣ εr ⎦ de = ———— (2.9) Z 0 er and under a slightly different value of Z 0 > (63 – 2er )Ω εr + 1 εr − 1 ⎛ h −0.555 εe = + 1 + 10 ⎞ (2.10) 2 2 ⎝ w⎠ Equations 2.3 to 2.10 are accurate up to about 2 GHz. For higher frequencies, the effect of frequency dependence of ee has to be taken into account. An expression often used to eval- uate ee(ƒ) as frequency (ƒ) varies is εr − εe εe ( f ) = εr − 1.33 (2.11) 1 + ( h Z0 ) (0.43 f 2 − 0.009 f 3 ) where h is in millimetres, ƒ is in gigahertz, and ee is the value calculated by either Equa- tion 2.7 or 2.10. Example 2.3 Two microstrip lines are printed on the same dielectric substrate. One line has a wider centre strip than the other. Which line has the lower characteristic impedance? Assume that there is no coupling between the two lines. Solution. If you refer to Equation 2.3 and examine the h/w ratio, you will see that Z 0 varies as a function of h/w. Therefore, the line with the lower characteristic impedance will have a wider centre conductor. As you can see for yourself, Equations 2.3 to 2.11 are rather complicated and should be avoided when possible. To avoid these types of calculations, we have included with this book a computer software program called PUFF. With this program, it is only necessary to decide on the characteristic impedance of the microstrip or stripline which we require and PUFF will do the rest. We will return to PUFF when we have explained the basic terms for using it. Expressions also exist for calculating the characteristic impedance of other lines such as the strip line, coplanar waveguide, slot line, etc. These are equally complicated but details of how to calculate them have been compiled by Gupta, Garg and Chadha.6 There is also a software program called AppCAD7 which calculates these impedances. 6 Gupta, K.C., Garg, R. and Chadha, R., Computer-Aided Design of Microwave Circuits, Artech House Inc, Norwood MA 02062 USA, ISBN: 0–89006–105–X. 7 AppCAD is a proprietary software program from the Hewlett Packard Co, Page Mill Road, Palo Alto CA, 54 Transmission lines Note: In the previous sections, I have produced equations which are peculiar to types of different transmission lines. From now on, and unless stated otherwise, all the equations in the sections that follow apply to all types of transmission lines. 2.5 Characteristic impedance (Z0) from primary electrical A typical twin conductor type transmission line is shown in Figure 2.8. Each wire conduc- tor has resistance and inductance associated with it. The resistance is associated with the material of the metal conductors, effective conductor cross-sectional area and length. The inductance is mainly dependent on length and type of material. In addition to these, there is capacitance between the two conductors. The capacitance is mainly dependent on the dielectric type, its effective permittivity, the effective cross-sectional area between conduc- tors, the distance between the conductors and the length of the transmission line. When a voltage is applied, there is also a leakage current between the two conductors caused by the non-infinite resistance of the insulation between the two conductors. This non-infinite resistance is usually expressed in terms of a shunt resistance or parallel conductance. Therefore, transmission lines possess inherent resistance, inductance, capacitance and conductance. It is very important to realise that these properties are distributed along the length of the line and that they are not physically lumped together. The lumped approach is only applicable when extremely short lengths of line are considered and as a practical line is made up of many short lengths of these lines, the lumped circuit equivalent of a transmission line would look more like that shown in Figure 2.8. This is an approximation but nevertheless it is an extremely useful one because it allows engineers to construct and simulate the properties of transmission lines. 2.5.1 Representation of primary line constants In Figure 2.8, let: R represent the resistance per metre (ohms/metre) L represent the inductance per metre (henry/metre) G represent the conductance per metre (siemen/metre) C represent the capacitance per metre (farad/metre) It follows that for a short length dl, we would obtain Rdl, Ldl, Gdl, and Cdl respectively. R jωL ⎞ δl = ⎛ + δl (2.12) 4 ⎝4 4 ⎠ Z1δl = ( R + jωL)δl (2.13) Ydl = (G + jwC)dl (2.14) Characteristic impedance (Z0) from primary electrical parameters 55 Fig. 2.8 Expanded view of a short section of transmission line Zδl = = (2.15) Yδ l (G + jωC )δ l 2.5.2 Derivation of line impedance The input impedance Z in of the short section dl when terminated by a matched line is given Zδ l ⎛ 1 δ l + Z0 + 1 δ l⎞ Z Z Z1 ⎝ 4 4 ⎠ Z1 Zin = δl + + δl 4 Z1 Z Zδ l + δ l + Z0 + 1 δ l 4 Since the line is terminated by another line, Z in = Z 0 Zδl ⎛ 1 δl + Z0 ⎞ Z1 ⎝ 2 ⎠ Zin = Z0 = δl + 2 Z1 Zδl + δl + Z0 8 The Z term in the centre fraction on the right-hand side of the equation is present because the short section of line (dl) is terminated by an additional line which presents an input impedance of Z 0. 56 Transmission lines Cross-multiplying, we get Z0 ⎛ Zδ l + 1 δ l + Z0 ⎞ = 1 δ l ⎛ Zδ l + 1 δ l + Z0 ⎞ + Zδ l ⎛ 1 δ l + Z0 ⎞ Z Z Z Z ⎝ 2 ⎠ 2 ⎝ 2 ⎠ ⎝ 2 ⎠ Z0 Z1 ZZ Z2 Z Z ZZ Z0 Zδ l + 2 δ l + Z0 = 1 δ l 2 + 1 δ l 2 + 0 1 δ l + 1 δ l 2 + ZZ0δ l Z1 2 Z0 = ZZ1δ l 2 + δl (2.16) Substituting for Z and Z1, we get 2 ( R + jωL)δ l ⎛ R jωl ⎞ 2 2 Z0 = + + δl (G + jωC )δ l ⎝ 4 4 ⎠ In the limit when dl → 0, and taking the positive square root term R + jωL Z0 = (2.17) G + jωC If you examine the expression for Z 0 a bit more closely, you will see that there are two regions where Z 0 tends to be resistive and constant. The first region occurs at very low frequencies when R jwL and G jwC. This results in Z0 ≈ (2.18) The second region occurs at very high frequencies when jwL R and jwC G. This results in Z0 ≈ (2.19) The second region is also known as the frequency region where a transmission line is said to be ‘lossless’ because there are ‘no’ dissipative elements in the line. Equation 2.19 is also useful because it explains why inductive loading, putting small lumped element inductors in series with lines, is used to produce a more constant imped- ance for the line. The frequency regions of operation described by Equations (2.18) and (2.19) are important because under these conditions, line impedance tends to remain frequency independent and a state known as ‘distortionless transmission’ exists. The distortionless condition is very useful for pulse waveform/digital transmissions because in these regions, frequency dispersion and waveform distortion tend to be minimal. These statements can also be verified by the following practical example. Characteristic impedance (Z0) from primary electrical parameters 57 Example 2.4 A transmission line has the following primary constants: R = 23 W km–1, G = 4 mS km–1, L = 125 µH km–1 and C = 48 nF km–1. Calculate the characteristic impedance, Z0, of the line at a frequency of (a) 100 Hz, (b) 500 Hz, (c) 15 kHz, (d) 5 MHz and (e) 10 MHz. Given: R = 23 W km–1, G = 4 mS km–1, L = 125 µH km–1 and C = 48 nF km–1. Required: Z 0 at (a) 100 Hz, (b) 500 Hz, (c) 15 kHz, (d) 5 MHz and (e) 10 MHz. Solution. Use Equation 2.17 in the calculations that follow. (a) At 100 Hz R + jwL = (23 + j0.08) W km–1, G + jwC = (4 + j0.030) mS km–1 23 + j0.08 Z0 = = 75.83Ω / − 2.06 × 10 −3 rad ( 4 + j0.030) × 10 −3 (b) At 500 Hz R + jwL = (23 + j0.39) W km–1, G + jwC = (4 + j0.15) mS km–1 23 + j0.39 Z0 = = 75.81Ω / − 10.30 × 10 −3 rad ( 4 + j0.15) × 10 −3 (c) At 15 kHz R + jwL = (23 + j11.78) W km–1, G + jwC = 4 + j4.52 mS km–1 23 + j11.78 Z0 = = 65.42Ω / − 0.19 rad ( 4 + j4.52) × 10 −3 (d) At 5 MHz R + jwL = (23 + j3926.99) W km–1, G + jwC = (4 + j1508) mS km–1 23 + j3926.99 Z0 = = 50.03Ω / − 0.00 rad ( 4 + j1508) × 10 −3 (e) At 10 MHz R + jwL = (23 + j7853.98) W km–1, G + jwC = (4 + j3016) mS km–1 23 + j7853.98 Z0 = = 50.03Ω / − 0.00 rad ( 4 + j3016) × 10 −3 58 Transmission lines Conclusions from Example 2.4. At low frequencies, i.e. 100–500 Hz, the line impedance Z 0 tends to remain at about 75 W with very little phase shift over a wide frequency range. For most purposes, it is resistive and constant in this region. See cases (a) and (b). At high frequencies, i.e. 5–10 MHz, the line impedance Z 0 tends to remain constant at about 50 W with little phase shift over a wide frequency range. For most purposes, it is resistive and constant in this region. See cases (d) and (e). In between the above regions, the line imped- ance Z0 varies with frequency and tends to be reactive. See case (c). For radio work, we tend to use transmission lines in the ‘lossless’ condition (Equation 2.19) and this helps considerably in the matching of line impedances. 2.6 Characteristic impedance (Z0) by measurement Occasions often arise when the primary constants of a line are unknown yet it is necessary to find the characteristic impedance (Z0). In this case, Z 0 can be obtained by measuring the short- and open-circuit impedance of the line. In Figures 2.9 and 2.10 as in Figure 2.8 let: R represent the resistance per metre (ohms/metre) L represent the inductance per metre (henry/metre) G represent the conductance per metre (siemen/metre) C represent the capacitance per metre (farad/metre) It follows that for a short length dl, we would obtain Rdl, Ldl, Gdl and Cdl respectively. Fig. 2.9 Open-circuit equivalent of a short length of transmission line 2.6.1 Open-circuit measurement (Zoc) Hence defining Zdl as l/Ydl we have Z1 Z Zoc = δ l + Zδ l + 1 δ l 4 4 (2.20) = δ l + Zδ l Characteristic impedance (Z0) by measurement 59 Fig. 2.10 Short-circuit equivalent of a short length of transmission line 2.6.2 Short-circuit measurement (Zsc ) The short-circuit impedance is Zδ l ⎛ 1 δ l + 1 δ l⎞ Z Z Z ⎝ 4 4 ⎠ Z Zsc = 1 δl + + 1 δl Zδ l + ⎛ Z1 δ l + Z1 δ l⎞ 4 ⎝ 4 4 ⎠ ZZ1 2 Z1 2 = δl + 2 Z Zδ l + 1 δ l Z1 ⎛ δ l Zδ l + 1 δ l⎞ + 1 δ l 2 Z ZZ 2 ⎝ 2 ⎠ 2 Zδ l + δ l Z1 2 ZZ1δ l 2 + δl = 4 Zδ l + 1 δ l Using Equation 2.16 to substitute for the numerator and Equation 2.20 to substitute for the denominator, we have 60 Transmission lines Z 02 Z sc = —— Z oc Z 02 = Z sc Z oc Z0 = Zsc Zoc (2.21) Example 2.5 The following measurements have been made on a line at 1.6 MHz where Z oc = 900 W /–30° and Z sc = 400 W /–10°. What is the characteristic impedance (Z 0) of the line at 1.6 Given: f = 1.6 MHz, Z oc = 900 W /–30° , Z sc = 400 W /–10°. Required: Z 0 at 1.6 MHz. Solution. Using Equation 2.21 Z0 = Zsc Zoc = 900 Ω / − 30° × 400 Ω / − 10° = 600 Ω / − 20° 2.7 Typical commercial cable impedances Manufacturers tend to make cables with the following characteristic impedances (Z 0). These are: • 50 Ω – This type of cable finds favour in measurement systems and most radio instru- ments are matched for this impedance. It is also used extensively in amateur radio Most cable manufacturers make more than one type of 50 Ω line. For example, you can buy 50 Ω rigid lines (solid outer connector), 50 Ω low loss lines (helical and air dielectrics), 50 Ω high frequency lines for use up to 50 GHz with minimal loss. The reason for this is that different uses require different types of lines. Remember that in Equation 2.1 repeated here for convenience Z0 = 138 log10 ( D d ) ε and the dimen- sion of the variables can be changed to produce the desired impedance. • 75 Ω – This type of cable is favoured by the television industry because it provides a close match to the impedance (73.13 Ω) of a dipole aerial. Most TV aerials are designed for this impedance and it is almost certain that the cable that joins your TV set to the external aerial will have this impedance. The comments relating to the different types of 50 Ω lines also apply to 75 Ω lines. Signal propagation on transmission lines 61 • 140 Ω – This type of cable is used extensively by the telephone industry. The comments relating to the different types of 50 Ω lines also apply to 140 Ω lines. • 300 Ω – This type of cable is favoured by both the radio and television industry because it provides a close match for the impedance (292.5 Ω) of a very popular antenna (folded dipole antenna) which is used extensively for VHF-FM reception. The comments relat- ing to the different types of 50 Ω lines also apply to 300 Ω lines. • 600 Ω – This type of cable is used extensively by the telephone industry and many of their instruments are matched to this impedance. The comments relating to the different types of 50 Ω lines also apply to 600 Ω lines. 2.8 Signal propagation on transmission lines 2.8.1 Pulse propagation on an infinitely long or matched transmission We are now going to use some of the ideas introduced in the previous sections, particularly Section 2.2.2, to describe qualitatively the propagation of signals along an infinitely long transmission line. In this description we will only make two assumptions: • the transmission line is perfectly uniform, that is its electrical properties are identical all along its length; • the line extends infinitely in one direction or is perfectly terminated. To keep the explanation simple, we will initially only consider the propagation of a single electrical pulse along the line9 shown in Figure 2.11. At the beginning of the line (top left hand corner) a voltage source (Vs) produces the single pulse shown in Figure 2.11. The waveforms shown at various planes (plane 1, plane 2, plane 3) on the line illustrate three of the main properties of signal propagation along a transmission line: • propagation delay – the pulse appears at each successive point on the line later than at the preceding point; • attenuation – the peak value of the pulse is attenuated progressively; • waveform distortion and frequency dispersion – its shape differs from its original shape at successive points. 2.8.2 Propagation delay The pulse appears later and later at successive points on the line because it takes time to travel over any distance, i.e. there is a propagation delay. As the line is uniform throughout 9 The behaviour of a pulse travelling along an infinitely long transmission line is very similar to the example you were given in Section 2.2.2 concerning sound travelling down an infinitely long tunnel except that this time instead of voice sounds, consider the sound to originate from a single drum beat or pulse. You will no doubt remember from earlier work that a pulse is a waveform which is made up from a fundamental sinusoid and its harmonics combined together in a precise amplitude, phase and time relationship. 62 Transmission lines Fig. 2.11 Pulse propagation in a transmission line its length, the amount of delay at any point is proportional to distance between that point and the source of the pulse. These time delays are shown as t1, t 2, and t 3 in Figure 2.11. Another way of describing this is to say that the pulse propagates along the line with a uniform velocity. 2.8.3 Attenuation The amplitude of the pulse is attenuated as it propagates down the line because of resis- tive losses in the wires. The amount of attenuation per unit length is uniform throughout the line because the line cross-section is uniform throughout the line length. Uniform attenuation means that the fractional reduction in pulse amplitude is the same on any line section of a given length. This is more easily understood by referring to Figure 2.11, where the pulse amplitude at plane 1 has been reduced by a factor of 0.8. At plane 2, which is twice as far from the source as plane 1, the pulse height has been reduced by a further factor of 0.8, i.e. a total of 0.82 or 0.64 of its original amplitude. At plane 3, which is three times as far from the source as plane 1, the reduction is 0.83 or 0.512 of the orig- inal amplitude. More generally, at a distance equal to l times the distance from the source to plane 1, the height is reduced by (0.8)l. Because l is the exponent in this expression this type of amplitude variation is called exponential. It can also be expressed in the form (eα)l or eαl, where ea represents the loss per unit length and is 0.8 in this particular example. In fact a is the natural logarithm of the amplitude reduction per unit length. Its unit is called the neper and loss (dB) = 8.686 nepers.10 Example 2.6 A transmission has a loss of two nepers per kilometre. What is the loss in dB for a length of 10 kilometres? Given: Attenuation constant (α) = 2 nepers per km. Required: Loss in dB for a length of 10 km. 10 This is because dB = 20 Log (Ratio) = 20 Log (ea) = 20 × a × Log (e) = 20 × a × 0.4343 = 8.686a. Waveform distortion and frequency dispersion 63 Solution. If 1 km represents a loss of 2 nepers, then 10 km = 10 × 2 = 20 nepers. There- loss = 8.686 × 20 = 173.72 dB 2.9 Waveform distortion and frequency dispersion 2.9.1 Amplitude distortion The waveform of the pulse in Figure 2.11 alters as it travels along the line. This shape alteration is caused by the line constants (inductance, capacitance, resistance and conduc- tance of the line) affecting each sinusoidal component of the waveform in a different manner. The high frequency components, which predominate on the edges of the pulse waveform, suffer greater attenuation because of increased reactive effects; the lower frequency components, which predominate on the flat portion of the waveform, suffer less attenuation. The variation of attenuation with frequency is described by the frequency response of the line. 2.9.2 Frequency distortion In addition to attenuation, there are also time constants associated with the line compo- nents (inductance, capacitance, resistance and conductance). These cause high frequency components to travel at a different velocity from low frequency components. The variation of velocity with frequency is called the frequency dispersion of the line. 2.9.3 Phase and group velocities As a pulse consists of sinusoidal components of different frequencies, each component will therefore be altered differently. Distinction must be made between the velocities of the sinusoidal components which are called phase velocities, up. The phase velocity (b) is defined as the change in radians over a wavelength and since there is a phase change of 2π radians in every wavelength, it follows that b = 2π radians/wavelength (l) b = —— (2.22) The velocity of the complete waveform is called the group velocity, ug. The apparent velocity of the pulse in Figure 2.11 is called its group velocity. It is important to realise that if the line velocity and line attenuation of all the compo- nent sinusoids which make up a pulse waveform are not identical then deterioration in pulse waveform shape will occur. Pulse distortion is particularly critical in high speed data transmission where a series of distorted pulses can easily merge into one another and cause pulse detection errors. If distortion occurs and if it is desired to know how and why a particular waveform 64 Transmission lines has changed its shape, it will be necessary to examine the propagation of the constituent sinusoids of the waveform itself and to instigate methods, such as frequency and phase equalisation, to ensure minimal waveform change during signal propagation through the 2.10 Transmission lines of finite length 2.10.1 Introduction In Section 2.8.1, we discussed waveforms travelling down infinitely long lines. In practice, infinitely long lines do not exist but finite lines can be made to behave like infinitely long lines if they are terminated with the characteristic impedance of the line.11 2.10.2 Matched and unmatched lines A transmission line which is terminated by its own characteristic impedance, Z 0, is said to be matched or properly terminated. A line which is terminated in any impedance other than Z 0 is said to be unmatched or improperly terminated. To prevent reflections it is usual for a transmission line to be properly terminated and so it is a common condition for a transmission line to behave electrically as though it was of infinite length. If a transmission line is to be used for signals with a wide range of frequency compo- nents, it may be difficult to terminate it properly. In general, the characteristic impedance of a transmission line will vary with frequency and if the matching load fails to match the line at all frequencies, then the line will not be properly terminated and reflections will In practice, it is usual to properly terminate both ends of a transmission line, i.e. both at the sending end and the receiving end; otherwise any signal reflected from the receiv- ing end and travelling back towards the sending end will be re-reflected again down the line to cause further reflections. The sending end can be properly terminated either by using a source generator with an impedance equal to the characteristic impedance of the line or by using a matching network to make a source generator present a matched imped- ance to the transmission line. 2.11 Reflection transmission coefficients and VSWR 2.11.1 Introduction Reflection coefficients are based on concepts introduced in your childhood. Consider the case when you throw a ball at a vertical stone wall. The ball with its incident power will 11 This argument is similar to the case mentioned in Section 2.2.2 where it was shown that if our finite tunnel was terminated with material with the same properties as an infinitely long tunnel which absorbed all the inci- dent energy then it would also behave like an infinitely long tunnel. 12 You see this reflection effect as multiple images on your television screen when the TV input signal is not properly terminated by the TV system. TV engineers call this effect ‘ghosting’. Reflection and transmission coefficients 65 travel towards the wall, hit the wall which will absorb some of its incident power and then the remaining power (reflected power) will cause the ball to bounce back. The ratio (reflected power)/(incident power) is called the reflection coefficient. The reflection coefficient is frequently represented by the Greek letter gamma (G). In mathe- matical terms, we have reflected power incident power This simple equation is very useful for the following reasons. • Its value is independent of incident power because if you double incident power, reflected power will also double.13 If you like, you can say that Γ is normalised to its incident power. • It gives you a measure of the hardness (impedance) of the wall to incident power. For example if the wall is made of stone, it is likely that very little incident power will be absorbed and most of the incident power will be returned to you as reflected power. You will get a high reflection coefficient (Γ → 1). If the wall is made of wood, it is likely that the wood would bend a bit (less resistance), absorb more incident energy and return a weaker bounce. You will get a lower reflection coefficient (Γ < 1). Similarly if the wall was made of straw, it is more than likely that most of the incident energy would be absorbed and there would be little rebounce or reflected energy (Γ → 0). Finally if the wall was made of air, the ball will simply go through the air wall and carry all its inci- dent power with it (G = 0). There will be no reflected energy because the incident energy would simply be expended in carrying the ball further. Note in this case that the trans- mission medium resistance is air, and it is the same as the air wall resistance which is the load and we simply say that the load is matched to the transmission medium. • By measuring the angle of the re-bounce relative to the incident direction, it is possible to tell whether the wall is vertical and facing the thrower or whether it is at an angle (phase) to the face-on position. Hence we can determine the direction of the wall. • The path through which the ball travels is called the transmission path. • Last but not least, you need not even physically touch the wall to find out some of its characteristics. In other words, measurement is indirect. This is useful in the measure- ment of transistors where the elements cannot be directly touched. It is also very useful when you want to measure the impedance of an aerial on top of a high transmitting tower when your measuring equipment is at ground level. The justification for this statement will be proved in Section 2.13. 2.11.2 Voltage reflection coefficient14 (Γv) in transmission lines The same principles described above can also be applied to electrical energy. This is best explained by Figure 2.12 where we have a signal generator with a source impedance, Z s, sending electrical waves through a transmission line whose impedance is Z 0, into a load impedance, Z L. 13 This of course assumes that the hardness of your wall is independent of the incident power impinging on Some authors use different symbols for voltage reflection coefficient. Some use Gv , while others use rv. In this book, where possible, we will use Gv for components and rv for systems. 66 Transmission lines Fig. 2.12 Incident and reflected waves on a transmission line If the load impedance (Z L) is exactly equal to Z 0, the incident wave is totally absorbed in the load and there is no reflected wave. If Z L differs from Z 0, some of the incident wave is not absorbed in the load and is reflected back towards the source. If the source imped- ance (Z s) is equal to Z 0, the reflected wave from the load will be absorbed in the source and no further reflections will occur. If Z s is not equal to Z 0, a portion of the reflected wave from the load is re-reflected from the source back toward the load and the entire process repeats itself until all the energy is dissipated. The degree of mis-match between Z 0 and Z L or Z s determines the amount of the incident wave that is reflected. By definition voltage reflection coefficient = ———— = Γv ∠ q (2.23) i reflected current reflection coefficient = ———— = Γi ∠ θ (2.24) i incident From inspection of the circuit of Figure 2.12 Z0 = (2.25) Z0 = (2.26) The minus sign in Equation 2.27 occurs because we use the mathematical convention that current flows to the right are positive, therefore current flows to the left are negative. ZL = vi + v r vi + v r v (1 + Γv ) = = = Z0 i (2.27) ii − ir vi Z 0 − v r Z 0 vi (1 − Γv ) Reflection and transmission coefficients 67 Sorting out terms in respect of Γv (1 + Gv) Z L = Z 0 —— —— (1 – Gv) (Z L – Z 0 ) Gv = ——— —— (2.28) (Z L + Z 0 ) Returning to Equation 2.24 and recalling Equation 2.23 ir – vr /Z 0 Γi = — = ———— = – Γv (2.29) ii vi /Z 0 As the match between the characteristic impedance of the transmission line Z 0 and the terminating impedance Z L improves, the reflected wave becomes smaller. Therefore, using Equation 2.28, the reflection coefficient decreases. When a perfect match exists, there is no reflected wave and the reflection coefficient is zero. If the load Z L on the other hand is an open or short circuit, none of the incident power can be absorbed in the load and all of it will be reflected back toward the source. In this case, the reflection coefficient is equal to 1, or a perfect mismatch. Thus the normal range of values for the magnitude of the reflection coefficient is between zero and unity. Example 2.7 Calculate the voltage reflection coefficient for the case where Z L = (80 – j10) Ω and Z 0 = 50 Ω. Given: ZL = (80 – j10), Z0 = 50Ω Required: Γv Solution. Using Equation 2.28 ZL – Z0 80 – j10 – 50 30 – j10 Γv = ———— = —————— = ———— ZL + Z0 80 – j10 + 50 130 – j10 31.62 ∠ –18.43° = ——————— = 0.24 ∠ –14.03° 130.38 ∠ –4.40° Example 2.8 Calculate the voltage reflection coefficients at the terminating end of a transmission line with a characteristic impedance of 50 Ω when it is terminated by (a) a 50 Ω termi- nation, (b) an open-circuit termination, (c) a short-circuit termination and (d) a 75 Ω 68 Transmission lines Given: Z 0 = 50 Ω, Z L = (a) 50 Ω, (b) open-circuit = ∞, (c) short-circuit = 0 Ω, (d) = 75 Required: Γv for (a), (b), (c), (d). Solution. Use Equation 2.28. (a) with Z L = 50 Ω ZL − Z0 50 − 50 Γv = = = 0 / 0° ZL + Z0 50 + 50 (b) with Z L = open circuit = ∞ Ω ZL − Z0 ∞ − 50 Γv = = = 1/ 0° ZL + Z0 ∞ + 50 (c) with Z L = short circuit = 0 Ω ZL − Z0 0 − 50 Γv = = = −1/ 0° or 1/180° ZL + Z0 0 + 50 (d) with Z L = 75 Ω ZL − Z0 75 − 50 Γv = = = 0.2 / 0° ZL + Z0 75 + 50 Example 2.8 is instructive because it shows the following. • If you want to transfer an incident voltage wave with no reflections then the terminating load (Z L) must match the characteristic impedance (Z 0) exactly. See case (a). This is the desired condition for efficient transfer of power through a transmission line. • Maximum in-phase voltage reflection occurs with an open circuit and maximum anti- phase voltage reflection occurs with a short circuit. See cases (b) and (c). This is because there is no voltage across a short circuit and therefore the reflected wave must cancel the incident wave. • Intermediate values of terminating impedances produce intermediate values of reflection coefficients. See case (d). 2.11.3 Return loss Incident power (Pinc) and reflected power (Pref) can be related by using the magnitude of the voltage reflection coefficient (G). Since G = vref /vinc, it follows that Pref vref Rload = 2 = Γ2 (2.30) Pinc Vinc Rload The return loss gives the amount of power reflected from a load and is calculated from: return loss (dB) = –10 log Γ 2 = –20 log Γ (2.31) Reflection and transmission coefficients 69 2.11.4 Mismatched loss The amount of power transmitted to the load (P L) is determined from PL = Pinc – Pref = Pinc(1 – Γ 2) (2.32) The fraction of the incident power not reaching the load because of mismatches and reflections is Pload P (2.33) = L = 1 − Γ2 Pincident Pinc Hence the mismatch loss (or reflection loss) is calculated from ML(dB) = –10 log (1 – Γ 2) (2.34) 2.11.5 Transmission coefficient The transmission coefficient (τv ) is defined as the ratio of the load voltage (vL) to the inci- dent voltage (vinc) but vL = vinc + vref . Hence vL v + vref τv = = inc = 1 + Γv (2.35) vinc vinc If we now use Equation 2.28 to substitute for Γv , we obtain Z L − Z0 2 ZL τ v = 1 + Γv = 1 + = (2.36) Z L + Z0 Z L + Z0 Sometimes Equation 2.36 is normalised to Z 0 and when Z L/Z 0 is defined as z, we obtain τv = (2.36a) z +1 Equation 2.36a is the form you frequently find in some articles. 2.11.6 Voltage standing wave ratio (VSWR) Cases often arise when the terminating impedance for a transmission line is not strictly within the control of the designer. Consider a typical case where a transmitter designed for operating into a 50 W transmission line is made to feed an antenna with a nominal imped- ance of 50 W. In the ideal world, apart from a little loss in the transmission line, all the energy produced by the transmitter will be passed on to the antenna. In the practical world, an exact antenna match to the transmission line is seldom achieved and most antenna manufacturers are honest enough to admit the discrepancy and they use a term called the voltage standing wave ratio15 to indicate the degree of mismatch. 15 This term is based on the Standing Wave Pattern principle which was introduced in Section 2.2.2 where you walked along a tunnel which produced echoes while your friend whistled at a constant amplitude and pitch. In the tunnel case, the loudest (maximum intensity) sound occurred where the incident and reflected wave added, while the weakest sound (minimum intensity) occurred where the incident and reflected sound opposed each other. 70 Transmission lines VSWR is useful because • it is relatively easy to measure – it is based on modulus values rather than phasor quan- tities which enables simple diode detectors to be used for measurement purposes; • it indicates the degree of mismatch in a termination; • it is related to the modulus of the reflection coefficient (shown later). Voltage standing wave ratio is defined as Vmax Vinc + Vref VSWR = = (2.37) Vmin Vinc − Vref A VSWR of |1| represents the best possible match.16 Any VSWR greater than |1| indi- cates a mismatch and a large VSWR indicates a greater mismatch than a smaller VSWR. Typical Figures of VSWRs for good practical terminations range from 1.02 to 1.1. Example 2.9 In Figure 2.12, the incident voltage measured along the transmission line is 100 V and the reflected voltage measured on the same line is 10 V. What is its VSWR? Soloution. Using Equation 2.37 Vinc + Vref 100 + 10 VSWR = = = 1.22 Vinc − Vref 100 − 10 2.11.7 VSWR and reflection coefficient (Γv ) VSWR is related to the voltage reflection coefficient by: Vinc + Vref Vinc 1 + Γv VSWR = = = (2.38) Vinc − Vref V 1 − Γv 1 − ref VSWR − 1 Γv = (2.38a) VSWR + 1 Example 2.10 What is the VSWR of a transmission system if its reflection coefficient |Γv| is 0.1? 16 In a properly terminated line, there are no reflections. V ref = 0 and substituting this value into Equation 2.37 |V inc| + |0| VSWR = ————— = |1| |V inc| – |0| Reflection and transmission coefficients 71 Given: |Γv| = 0.1 Required: VSWR Solution. Using Equation 2.38 1 + Γv 1 + 0.1 VSWR = = = 1.22 1 − Γv 1 − 0.1 Perfect match occurs when VSWR = |1|. This is the optimum condition and examination of Equation 2.38 shows that this occurs when |Γv | = 0. With this condition, there is no reflection, optimum power is transferred to the load and there are no standing wave patterns on the line to cause excessive insulation breakdown or electrical discharges to surrounding conductors and there are no ‘hot spots’ or excessive currents on sections of the Example 2.11 A manufacturer quotes a maximum VSWR of 1.07 for a resistive load when it is used to terminate a 50 Ω transmission line. Calculate the reflected power as a percentage of the incident power. Given: VSWR = 1.07, Z0 = 50 W Required: Reflected power as a percentage of incident power Solution. Using Equation 2.38a VSWR – 1 |Γv | = ————— = 0.034 VSWR + 1 Since power is proportional to V2 Pref = (0.034)2 × Pinc = 0.001 × Pinc = 0.1% of Pinc From the answer to Example 2.11, you should now realise that: • a load with an SWR of 1.07 is a good terminating load; • there are hardly any reflections when a transmission line is terminated with such a load; • the transmission line is likely to behave like an infinitely long line. 2.11.8 Summary of Section 2.11 If a transmission line is not properly terminated, reflections will occur in a line. These reflections can aid or oppose the incident wave. In high voltage lines, it is possible for the aiding voltages to cause line insulation breakdown. In high current lines, it is possible at high current points for aiding currents to overheat or even destroy the metallic conductors. The voltage reflection coefficient (Γv ) can be calculated by reflected voltage wave ZL − Z0 Γv = = incident voltage wave ZL + Z0 72 Transmission lines Manufacturers tend to use VSWRs when quoting the impedances associated with their equipment. A VSWR of |1| is the optimum condition and indicates that a perfect match is possible and that there will be no reflections when the equipment is matched to a perfect transmission line. VSWR can be calculated from the reflection coefficients by Vmax V + Vref 1 + Γv VSWR = = inc = Vmin Vinc − Vref 1 − Γv The return loss is a way of specifying the power reflected from a load and is equal to –10 log Γ 2. The mismatch loss or reflection loss specifies the fraction of incident power not reaching the load and is equal to –10 log (1 – Γ 2). 2.12 Propagation constant (γ) of transmission lines 2.12.1 Introduction In Section 2.8, we saw that signals on transmission lines suffer attenuation, phase or time delay, and often frequency distortion. In this section, we will show the relationships between these properties and the primary constants (R, G, L and C) of a transmission line. 2.12.2 The propagation constant (γ) in terms of the primary constants To find the propagation constant (g) we start with the same equivalent circuit (Figure 2.8) used for the derivation of Z 0. It is re-drawn in Figure 2.13 with the voltage and current phasors indicated. The propagation constant, as defined, relates V2 and V1 by — = e–γδ l — (2.39) Fig. 2.13 Equivalent circuit of a very short length of line Propagation constant (γ) of transmission lines 73 where δ l is still the short length of line referred to in Figure 2.8. It is easier to find γ using the current phasors rather than the voltage phasors; so, using I1 = V1/Z 0 and I2 = V2 /Z 0 — = e–γδ l (2.40) or alternatively — = eγδl (2.40a) The current I1 splits into two parts: I2 and a part going through Z 2. By the current divider rule, the split is I2 = —————— I1 — Z 2 + Z 1/2 + Z 0 I1 Z Z = 1+ 1 + 0 I2 2 Z2 Z2 Substituting the definitions for Z 1 and Z 2 and the formula for Z 0 derived above gives I1 1 = 1 + ( R + jjωL)(G + jjωL)(δll )2+ (( R++jωLL)(G +jωL))δ l ( R + ωL)(G + ωL )(δ )2 + R jω )(G + jεL δl I2 2 = 1 + ( R + jωL)(G + jωL)δ l + ( R + jωL)(G + jωL)(δ l )2 Also I1/I2 = eγδ l. To use these two expressions for I1/I2 to find γ, we must first expand eγδ l into a Taylor series. Since ex = 1 + x + — + . . . we can write eγδ l as γ 2 (δ l )2 eγδ l = 1 + γδ l + +… Equating the two expressions for I1/I2 gives 1 + γδ l + γ 2 (δ l )2 2 = 1 + ( R + jωL)(G + jωL)δ l + ( R + jωL)(G + jωL)(δ l )2 Subtracting 1 from each side and dividing by δ l gives γδ l + γ 2 (δ l )2 2 = ( R + jωL)(G + jωL)δ l + ( R + jωL)(G + jωL)(δ l )2 74 Transmission lines and as δ l approaches zero γ = ( R + jωL)(G + jωL) (2.41) Since γ is complex consisting of a real term α for amplitude and β for phase, we can also γ = α + jβ = ( R + jωL)(G + jωL) (2.42) If the expression for γ (Equation 2.42) is examined more closely, it can be seen that there are two regions where γ tends to be resistive and constant. The first region occurs at very low frequencies when R j ωL and G j ωC. This results in γ ≈ ( R)(G) (2.43) In this region γ is a real number which does not depend on ω. Since the real part of g is a, the attenuation index, there is no amplitude distortion in the very low frequency range. The second region occurs at very high frequencies when j ωL R and j ωC G. This results in γ ≈ jω ( L)(C ) (2.44) In this region γ is purely imaginary and is proportional to ω. Since the imaginary part of γ is β, the phase index, it means that there is no dispersion (because β is proportional to ω) in the high frequency range. The region is very useful for pulse waveform/digital transmissions because in it frequency dispersion and waveform distortion tend to be Equation 2.44 is also useful because it explains why inductive loading, putting small lumped element inductors in series with lines, is sometimes used to reduce dispersion in Example 2.12 A transmission line has the following primary constants: R = 23 Ω km–1, G = 4 mS km–1, L = 125 µH km–1 and C = 48 nF km–1. Calculate the propagation constant γ of the line, and the characteristic impedance Z 0 of the line at a frequency of (a) 100 Hz, (b) 500 Hz, (c) 15 kHz, (d) 5 MHz and (e) 10 MHz. Solution. The characteristic impedance Z 0 will not be calculated here because it has already been carried out in Example 2.4. However, the results will be copied to allow easy comparison with the propagation results calculated here for the discussion that follows after this answer. Equation 2.41 will be used to calculate the propagation constant γ, and Equation 2.42 will be used to derive the attenuation constant α and the phase constant β in all the calculations that follow. (a) At 100 Hz R + jω L = (23 + j(2π × 100 × 125 µH)) = (23 + j0.08) Ω km–1 G + jwC = (4 mS + j(2π × 100 × 48 nF)) = (4 + j0.030) mS km–1 Propagation constant (γ) of transmission lines 75 γ = (23 + j0.08)( 4 + j0.030) × 10 −3 ) = 0.30 / 0.01 = (0.30 nepers + 1.66 × 10 −3 rad) km −1 23 + j0.08 Z0 = = 75.83Ω / − 2.06 × 10 −3 rad ( 4 + j0.030) × 10 −3 (b) At 500 Hz R + jwL = (23 + j(2π × 500 × 125 µH)) = (23 + j0.39) Ω km–1 G + j ωC = (4 mS + j(2π × 500 × 48 nF)) = (4 + j0.15) mS km–1 γ = (23 + j0.39)( 4 + j0.15) × 10 −3 = 0.30 / 0.03 rad = (0.30 nepers + 8.31 × 10 −3 rad) km −1 23 + j0.39 Z0 = = 75.82Ω / − 10.30 × 10 −3 rad ( 4 + j0.15) × 10 −3 (c) At 15 kHz R + j ω L = (23 + j(2π × 15 × 103 × 125 µH)) = (23 + j11.78) Ω km–1 G + j ω C = (4 mS + j(2π × 15 × 103 × 48 nF)) = (4 + j4.52 × 10–3) mS km–1 γ = (23 + j11.78)( 4 + j4.52) × 10 −3 = 0.40 / 0.66 rad = (0.31 nepers + 242 × 10 −3 rad) km −1 23 + j11.78 Z0 = = 65.42Ω / − 0.19 rad ( 4 + j4.52) × 10 −3 (d) At 5 MHz R + j ω L = (23 + j(2π × 5 × 106 × 125 µH)) = (23 + j3926.99) Ω km–1 G + j ω C = (4 mS + j(2π × 5 × 106 × 48 nF)) = (4 + j1508) mS km–1 76 Transmission lines γ = (23 + 3926.99)( 4 + j1508) × 10 −3 = 76.95/ 1.567 rad = (0.33 nepers + 76.95 rad) km −1 23 + j3926.99 Z0 = = 50.03Ω / − 0.00 rad ( 4 + j1508) × 10 −3 (e) At 10 MHz R + j ωL = (23 + j(2π × 10 × 106 × 125 µH) = (23 + j7853.98) Ω km–1 G + j ωC = (4 mS + j(2π × 10 × 106 × 48 nF)) = (4 + j3016) mS km–1 γ = (23 + j7853.98)( 4 + j3016) × 10 −3 = 153.91/ 1.569 rad = (0.33 nepers + j153.9 rad) km −1 23 + j7853.98 Z0 = = 50.03Ω / − 0.00 rad ( 4 + j3016) × 10 −3 Conclusions from Example 2.12. In the frequency range 100–500 Hz, the attenuation constant α tends to remain at about 0.30 nepers per km and the phase propagation β increases linearly with frequency. See cases (a) and (b). If you now compare this set of results with the same cases from Example 2.4, you will see that in this fre- quency range, Z 0 and α tend to remain constant and β tends to vary linearly with What this means is that if you transmit a rectangular pulse or digital signals in this frequency range, you will find that it will pass through the transmission line attenuated but with its shape virtually unchanged. The reason for the waveform shape not changing is because the Fourier amplitude and phase relationships have not been changed. In the frequency range 5–10 MHz, the attenuation constant α tends to remain at 0.33 nepers per km and the phase propagation β also increases linearly with frequency. See cases (d) and (e). If you now compare the above set of cases from Example 2.12 with an identical set from Example 2.4, you will see that within these frequency ranges, Z 0 and α tend to remain constant and β tends to vary linearly with frequency. Therefore the same argument in the foregoing paragraphs applies to this frequency range. This is also known as the ‘distortionless’ range of the transmission line. In the intermediate frequency range of operation (see case (c) of Examples 2.4 and 2.12), both the propagation constant α and β, and the characteristic impedance of the line Z 0 vary. Fourier amplitude and phase relations are not maintained as waveforms are trans- mitted along the line and waveform distortion is the result. Transmission lines as electrical components 77 2.12.3 Summary of propagation properties of transmission lines There are two frequency regions where signals can be passed through transmission lines with minimum distortion; a low frequency region and a high frequency region. The low frequency region occurs when R ω L, and G ω C. The high frequency region occurs when ω L R and ω C G. The high frequency region is also sometimes called the ‘loss- less’ region of transmission. At both these high and low frequency regions of operation, the simplified expressions for Z 0 (Equations 2.18 and 2.19) and γ (Equations 2.43 and 2.44) show that there is little distor- tion and that the transmission line can be more easily terminated by a matched resistor. Good cables which operate up to 50 GHz are available. They are relatively costly because of the necessary physical tolerances required in their manufacture. 2.13 Transmission lines as electrical components Transmission lines can be made to behave like electrical components, such as resistors, inductors, capacitors, tuned circuits and transformers. These components are usually made by careful choice of transmission line characteristic impedance (Z 0), line length (l) and termination (Z L). The properties of these components can be calculated by using well known expressions for calculating the input impedance of a transmission line. 2.13.1 Impedance relations in transmission lines We shall now recall some transmission line properties which you learnt in Sections 2.11.2 and 2.12.2 to show you how the input impedance varies along the line and how transmis- sion lines can be manipulated to produce capacitors, inductors, resistors and tuned circuits. These are Equations 2.28 and 2.29 which are repeated below for convenience: Z L − Z0 Γv = (2.28) Z L + Z0 Γi = –Γv (2.29) In previous derivations, voltages and currents references have been taken from the input end of the line. Sometimes, it is more convenient to take voltage and current references from the terminating or load end of the line. This is shown in Figure 2.14. From the definition of line attenuation and for a distance l from the load, we have v i = ViL e+γ l (2.45) vr = VrL e–γ l (2.46) and using the definition for voltage reflection coefficient Γv Vrl VrL e −γ l VrL Γvl = = = = ΓL e −2γ l (2.47) Vil VrL e +γ l ViL 78 Transmission lines Fig. 2.14 Line voltages reference to the load end l = line length equal to distance l Γv = voltage reflection coefficient at load Γvl = voltage reflection coefficient at distance l from load γ = propagation constant = (α + j β) nepers/m At any point on a transmission line of distance l from the load vl = v i + v r = v i + vi Γv e–2γ l (2.48) i l = i i + i r = i i + i i Γi e–2γ l (2.49) Dividing Equation 2.48 by Equation 2.49 and using Equations 2.28 and 2.29 vl vi + vi Γv e −2γ l il ii − ii Γv e −2γ l vi (1 + Γv e −2γ l ) = (2.50) ii (1 − Γv e −2γ l ) Defining Z l as impedance at point l, and Z 0 as the line characteristic impedance, Equa- tion 2.50 becomes 1 + Gv e–2gl Zl = Z0 [ ————— 1 – Gv e–2gl ] (2.51) Substituting equation 2.28 in equation 2.51 results in [ ] ZL – Z0 1 + ———— e–2gl ZL + Z0 Zl = Z0 ————————— ZL – Z 0 1 – ————— e–2gl ZL + Z0 Transmission lines as electrical components 79 Multiplying out and simplifying Z L + Z 0 + (Z L – Z 0) e–2gl Zl = Z 0 [ ——————————— Z L + Z 0 – (Z L – Z 0) e–2gl ] Sorting out Z 0 and Z L gives Z L(1 + e–2gl ) + Z 0 (1 – e–2gl ) Zl = Z 0 [ ———————————— Z L(1 – e–2gl ) + Z 0 (1 + e–2gl ) ] Multiplying all bracketed terms by (egl/2) results in egl – e–gl egl + e–gl Zl = Z0 [ Z 0 ———— + Z L ———— gl + e–gl gl – e–gl Z 0 ———— + Z L ———— Bear in mind that by definition egl – e–gl egl + e–gl sinh gl = ———— and cosh gl = ———— Substituting for sinh gl and cosh gl in the above equation results in Z 0 sinh gl + Z L cosh gl Z l = Z 0 —————————— Z 0 cosh gl + Z L sinh gl ] (2.52) Equation 2.52 is a very important equation because it enables us to investigate the proper- ties of a transmission line. If the total length of the line is l then Z l becomes the input impedance of the line. Hence, Equation 2.52 becomes Z 0 sinh gl + Z L cosh gl Z in = Z 0 [ —————————— Z 0 cosh gl + Z L sinh gl ] (2.53) 2.13.2 Input impedance of low loss transmission lines From Equation 2.42, we know that g = a + jb. When a << b, g = jb. From Equation 2.22, we know that b = 2π/l. From mathematical tables17 we know that sin (jb) = j sin b and cos(jb) = cos b. If we now substitute the above facts into Equation 2.53, we will get Equation 2.54. The input impedance of a low loss transmission line is given by the expression 17 You can also check this for yourself if you take the series for sin x and cos x and substitute jb in place of 80 Transmission lines [ ] 2πl 2πl jZ 0 sin —— + Z L cos —— l l Z in = Z 0 ————————————— (2.54) 2πl 2πl jZ L sin —— + Z 0 cos —— l l Z in = input impedance (ohms) Z0 = characteristic impedance of line (ohms) ZL = termination load on line (ohms) l = electrical wavelength at the operating frequency l = transmission line length 2.13.3 Reactances using transmission lines A transmission line can be made to behave like a reactance by making the terminating load a short circuit (Z L= 0). In this case, Equation 2.54 becomes [ ][ ] 2πl 2πl jZ 0 sin —— + 0 j sin —— l l 2πl Z in = Z 0 ———————— = Z 0 ————— = jZ 0 tan —— (2.55) 2πl 2πl l 0 + Z 0 cos —— cos —— l l When l < l/4 Z in = jZ 0 tan — — (2.55a) and is inductive. When l /4 < l > l/2 Z in = –jZ 0 tan — — (2.55b) and is capacitive. Equation 2.55 follows a tangent curve and like any tangent curve it will yield positive and negative values. Therefore Equation 2.55 can be used to calculate inductive and capacitive reactances. Adjustment of Z 0 and line length, l, will no doubt set the required Example 2.13 A 377 W transmission line is terminated by a short circuit at one end. Its electrical length is l/7. Calculate its input impedance at the other end. Transmission lines as electrical components 81 Solution. Using Equation 2.55a 2π l [ ] Z in = jZ 0 tan —— = j377 tan — — — = j377 × 1.254 = j472.8 W l l 7 Similar reactive effects can also be produced by using an open-circuited load18 and apply- ing it to Equation 2.54 to produce inductive and capacitive reactances: Z in = –jZ 0 cot —— (2.56) Equation 2.56 follows a cotangent curve and will therefore also produce positive and nega- tive impedances. Adjustment of Z0 and line length will set the required reactance. Example 2.14 A 75 W line is left unterminated with an open circuit at one end. Its electrical length is l/5. Calculate its input impedance at the other end. Solution. Using Equation 2.56 2πl 2π l Z in = –jZ 0 cot — = –j75 cot — — = –j75 × 0.325 = –j24.4 W — — l l 5 2.13.4 Transmission lines as transformers An interesting case arises when l = l/2. In this case Equation 2.54 becomes jZ 0 sin π + Z L cos π Z in = Z 0 [ ————————— = Z L jZ L sin π + Z 0 cos π ] What this means is that the transmission line acts as a 1:1 transformer which is very useful for transferring the electrical loading effect of a termination which cannot be placed in a particular physical position. For example, a resistor dissipating a lot of heat adjacent to a transistor can cause the latter to malfunction. With a 1:1 transformer, the resistor can be physically moved away from the transistor without upsetting electrical operating conditions. Another interesting case arises when l = l/4. In this case, Equation 2.54 becomes [ ] π π jZ 0 sin — + Z L cos — 2 2 Z 02 Z in = Z 0 —————————— = —— π π ZL Z L jsin — + Z 0 cos — 18 Purists might argue that an open circuit does not exist at radio frequencies because any unterminated TX line has stray capacitance associated with an open circuit. We will ignore this stray capacitance temporarily because, for our frequencies of operation, its reactance is extremely high. 82 Transmission lines Therefore the transmission line behaves like a transformer where Z 02 Z in = —— (2.57) At first glance Equation 2.57 may not seem to be very useful but if you refer back to Figure 2.7, you will see that the characteristic impedance (Z 0) of microstrip transmission lines can be easily changed by changing its width (w); therefore impedance matching is a very prac- tical proposition. Example 2.15 A transmission line has a characteristic impedance (Z 0) of 90 W. Its electrical length is l/4 and it is terminated by a load impedance (Z L) of 20 W. Calculate the input impedance (Z in) presented by the line. Given: Z0 = 90 W, ZL = 20 W, l = l/4 Required: Zin Solution. Using Equation 2.57 Z in = (90)2/20 = 405 W 2.14 Transmission line couplers Transmission lines can be arranged in special configurations to divide an input signal at the input port into two separate signals at the output ports. Such an arrangement is often called a signal splitter. Since the splitter is bi-directional, the same arrangement can also be used to combine two separate signals into one. These splitter/combiners are often called couplers. The advantages of couplers are that they are very efficient (low loss), provide good matching on all ports, and offer reasonable isolation between the output ports so that one port does not interfere with the other. The greatest disadvantage of these couplers is their large physical size when used in their distributed forms. 2.14.1 The branch-line coupler The basic configuration of the branch-line coupler is shown in Figure 2.15. It consists of transmission lines, each having a length of l/4. Two opposite facing-lines have equal Fig. 2.15 A branch-line coupler Transmission line couplers 83 impedances, Z 0, and the remaining opposite facing-lines have an impedance of Z 0/ 2. In the case of a 50 W coupler, Z 0 = 50 W and Z 0 / 2 = 35.355 W. Principle of operation All ports are terminated in Z 0. Signal is applied to port 1 and it is divided equally between ports 2 and 3. There is no output signal from port 4 because the path from port 1 to 4 is l/4 while the path from port 1 to 4 via ports 2 and 3 is 3l/4. The path difference is l/2; hence the signals cancel each other at port 4. The net result is that the signal at port 4 is zero and it can be considered as a virtual earth point. With this virtual earth point Figure 2.15 becomes Figure 2.16(a). We know from transmission line theory (Equation 2.57) that for a l/4 length, Z in = Z 02/Zl. In other words, a short circuit at port 4 appears as open circuits at port 1 and 3. This result is shown in Figure 2.16(b). If we now transform the impedance at port 3 to port 2, we get Z(transformed) = Z 02/Z 0 = Z 0 Hence we obtained the transformed Z 0 in parallel with the Z 0 termination of port 2. This situation is shown in Figure 2.16(c). We now need to transform the Z 0 /2 termination at port 2 to port 1. At port 1 (Z 0 / 2) 2 Z 02 2 Zl = ———— = —— × — = Z 0 (Z 0 /2) 2 Z0 This condition is shown in Figure 2.16(d). Fig. 2.16(a) Virtual short circuit at port 4 Fig. 2.16(b) Effect of virtual short circuit at port 4 84 Transmission lines Fig. 2.16(c) Effect of port 3 transferred to port 2 Fig. 2.16(d) Effect of port 2 transferred to port 1 We conclude that the hybrid 3 dB coupler provides a good match to its source imped- ance Z 0. Assuming lossless lines, it divides its signal equally at ports 2 and 3. Since signal travels over l/4 to port 2, there is a phase delay of 90° at port 2 and another 90° phase delay from port 2 to port 3. Thus the signal arriving at port 3 suffers a delay of 180° from the signal at port 1. The response of such a coupler designed for 5 GHz is shown in Figure 2.17. As you can see for yourself, the signal path from port 1 to port 2 (S21) is 3 dB down at 5 GHz. This is also true of the signal response to port 3 (S31). The signal attenuation to port 4 is theoret- ically infinite but this value is outside the range of the graph. A similar analysis will show that power entering at port 2 will be distributed between ports 1 and 4 and not at port 3. A similar analysis for port 3 will show power dividing between ports 1 and 4 but not at port 2. The net result of this analysis shows that signals Fig. 2.17 Unadjusted response of the quadrate 3 dB coupler: S21 = signal attenuation path from port 1 to port 2; S31 = signal attenuation path from port 1 to port 3; S41 = signal attenuation path from port 1 to port 4 Transmission line couplers 85 into port 2 and 3 are isolated from each other. This is a very useful feature in mixer and amplifier designs. The advantage of the quadrature coupler is easy construction but the disadvantage of this coupler is its narrow operational bandwidth because perfect match is only obtained at the design frequency where each line is exactly l/4 long. At other frequencies, each line length is no longer l/4 and signal attenuation increases while signal isolation decreases between the relevant ports. Finally, you may well ask ‘if port 4 is at virtual earth, why is it necessary to have a matched resistor at port 4?’ The reason is that signal balance is not perfect and the resistor helps to absorb unbalanced signals and minimises reflections. 2.14.2 The ring coupler Ring forms of couplers have been known for many years in waveguide, coaxial and stripline configurations. The basic design requirements are similar to that of the quadrature coupler except that curved lines are used instead of straight lines. One such coupler is shown in Figure 2.18. The principle of operation of ring couplers is similar to that of branch-line or quadrature couplers. Fig. 2.18 The 3 dB ring-form branch-line directional coupler 2.14.3 The ‘rat-race’ coupler A sketch of a ‘rat-race’ coupler is shown in Figure 2.19. The mean circumference of the ring is 1.5l. This coupler is easy to construct and provides good performance for narrow band frequencies. The characteristic impedance of the coupler ring is Z 0 2 W which in the case of Z 0 = 50 W is a circular 70.7 W transmission line which is 1.5l in circumference. The four Z 0 ports are connected to the ring in such a manner that ports 2 to 3, ports 3 to 1 and ports 1 to 4 are each separated by l/4. Port 4 to port 2 is separated by 0.75l. The oper- ation of this device is illustrated in Figure 2.20. If a signal is injected at port 1, the voltage appearing at port 2 is zero, since the path lengths differ by 0.5l; thus port 2 can be treated as a virtual ground. Hence the transmis- sion-line portions of the ring between ports 2 and 3, and ports 2 and 4, act as short- circuited stubs connected across the loads presented at ports 3 and 4. For centre frequency 86 Transmission lines Fig. 2.19 The ‘rat-race’ or ‘hybrid ring’ coupler Fig. 2.20 (a) Equivalent circuit of ring hybrid with port 1 as input and ports 2 and 4 as outputs (transmission-line model with port 3 as virtual ground); (b) equivalent circuit at centre frequency operation, these stubs appear as open circuits. Similarly, the transmission line lengths between ports 3 and 1, and ports 4 and 1, transform the 50 W load impedances at ports 3 and 4 to 100 W (2 Z 0) at port 1. When combined at port 1, these transformed impedances produce the 50 W impedance at port 1. See Figure 2.20(a) and (b). A similar analysis can be applied at each port, showing that the hybrid exhibits a matched Summary 87 impedance of 50 W or Z 0 at all nodes. It should be noted that when port 1 is driven, the outputs at ports 3 and 4 are equal and in phase, while ideally there is no signal at port 2. However, when port 2 is driven, the output signals appearing at ports 3 and 4 are equal but exactly out of phase. Also there is no signal at port 1. Hence ports 1 and 2 are isolated. This is very useful especially in signal mixing circuits because it enables two slightly different frequencies, for example ƒ1 at port 1 and ƒ2 at port 2, to be applied to a balanced mixer whose diodes may be connected to ports 3 and 4 without coupling between the sources at port 1 and port 3. It also helps to combine the inputs or outputs of two amplifiers without mutual inter- ference. The unfortunate thing about the ring is that it is a relatively narrow-band device. 2.15 Summary Chapter 2 has provided you with a thorough basic knowledge of transmission lines and their properties which you will find very useful in circuit and system design of radio and microwave systems. You have been introduced to many properties of transmission lines in this chapter. In Section 2.3, you were introduced to some of the more frequently used types of trans- mission lines. These included waveguides, coplanar waveguides, coaxial lines, microstrip and strip lines, slot lines, twin lines and finally coupled microstrip lines. In Section 2.4, you were shown how the characteristic impedance of the coaxial, twin line and microstrip line can be calculated from its physical parameters. The information demonstrated what properties you should look for if the characteristic impedance of a line does not behave as expected. Sections 2.5 and 2.6 demonstrated how the characteristic impedance can be calculated and measured from primary constants of the line. Section 2.7 mentions some of the more common impedances associated with commercial transmission lines but it also brought to your attention that there are many types of lines with the same impedance. Section 2.8 explained how propagation delay, attenuation and frequency dispersion affect waveforms as they travel along transmission lines. This was followed by more discussions on the effects of these properties in Section 2.9. In Section 2.10, we introduced the concepts of matched and unmatched lines. This was followed by a thorough discussion of reflection coefficients and voltage standing wave ratios in Section 2.11. Section 2.12 dealt with the propagation properties of lines and showed how these can be derived from the primary constants of the line. The section also showed how optimum transmission can be achieved. Section 2.13 showed how transmission lines can be used as transformers, impedance matching devices, inductive and capacitive reactances which in turn can be used to produce filters. Microstrip lines are particularly useful for making filters at the higher frequencies because of their versatility in allowing characteristic impedance changes to be made easily. There is also a greater tendency to use transmission lines as the tuning elements. Section 2.14 showed you how transmission lines can be connected to act as signal Finally, you will come across these examples again when we introduce the software program PUFF in Chapter 4 and carry out some examples to further clarify your theory and the use of the program. Smith charts and scattering 3.1 Introduction 3.1.1 Aims The aims of this part are to familiarise you with two fundamental necessities in radio engi- neering; Smith charts and scattering parameters. We start with Smith charts because they are very useful for amplifier design, gain circles, noise circles, matching network design, impedance and admittance determination and finding reflection coefficients and voltage standing wave ratios. Scattering parameters are important because many basic items such as filters, hybrid transformers, matching networks, transistors, amplifiers, gain blocks and monolithic microwave integrated circuits (MMIC) are used and described by manufacturers in terms of two port networks. You also need s-parameters for circuit and system design. In this part, Sections 3.2 to 3.4 have been devoted to a description of the Smith chart. Section 3.5 covers its theory and Sections 3.6 to 3.9 provide examples on Smith chart applications. Section 3.10 deals with the fundamentals of scattering parameters and Section 3.11 gives examples of its applications. 3.1.2 Objectives After reading the section on Smith charts, you should be able to: • evaluate impedance and admittance networks; • design impedance and admittance networks; • design matching networks. After reading the section on scattering parameters, you should be able to: • understand scattering parameters; • use two port scattering parameters efficiently; • design two port scattering networks; • evaluate two port scattering networks; • calculate the frequency response of networks; • calculate the gain of two port networks or an amplifier; • calculate the input impedance of two port networks or an amplifier; • manipulate two port data into other types of parameter data. Smith charts 89 3.2 Smith charts 3.2.1 Introduction The Smith chart is intended to provide a graphical method for displaying information, for impedance matching using lumped and distributed elements and is particularly useful in solving transmission line problems. It avoids the tedious calculations involved in applying the expressions obtained and proved in Part 2. It is an alternative check to your calcula- tions and provides a picture of circuit behaviour to help you visualise what happens in a Fig. 3.1 Smith chart 90 Smith charts and scattering parameters circuit. The Smith chart1 was devised by P.H. Smith in the late 1930s and an improved version was published in 1944. It is shown in Figure 3.1. The Smith chart is based on two sets of circles which cut each other at right-angles. One set (Figure 3.2) represents the ratio R/Z 0, where R is the resistive component of the line impedance Zx = R + jX. Z 0 is usually taken as the characteristic impedance of a transmis- sion line. Sometimes Z 0 is just chosen to be a number that will provide a convenient display on the Smith chart. The other set of circles (Figure 3.3) represents the ratio jX/Z 0, Fig. 3.2 Resistive circles of 0, 0.2, 0.4, 1, 2, 4 and 20 are shown in bold 1 The Smith chart is a copyright of Analog Instruments Co., P.O. Box 808, New Providence, NJ07974, USA. Smith charts 91 where X is the reactive component of the line impedance Zx = R + jX. Z 0 is usually taken as the characteristic impedance of a transmission line. Sometimes Z 0 is just chosen to be a number that will provide a convenient display on the Smith chart. In both cases of normalisation, the same number must be used for both resistance and reactance normali- sation. The circles have been designed so that conditions on a lossless line with a given VSWR can be found by drawing a circle with its centre at the centre of the chart. Figures 3.1, 3.2 and 3.3 are full detailed versions of the Smith chart. When electronic versions of the chart are used, such detail tends to clutter a small computer screen. In such cases, it is best to show an outline Smith chart and to provide the actual coordinates in complex numbers. This is the system which has been used by the software program PUFF, Fig. 3.3 Reactance arcs of circles for j = ±0, 0.2, 0.4, 1, 2, 4 92 Smith charts and scattering parameters provided with this book. There is also another Smith chart program called MIMP2 (Motorola Impedance Matching Program). 3.2.2 Plotting impedance values Any point on the Smith chart represents a series combination of resistance and reactance of the form Z = R + jX. Thus, to locate the impedance Z = 1 + jl, you would find the R = 1 constant resistance circle and follow it until it crosses the X = 1 constant reactance circle. The junction of these two circles would then represent the needed impedance value. This particular point, A shown in Figure 3.4, is located in the upper half of the chart because X is a positive reactance or inductive reactance. On the other hand, the point B which is 1 – jl is Fig. 3.4 Some values on a simplified Smith chart 2 At the time of writing, this program can be obtained free from some authorised Motorola agents. This program provides active variable component matching facilities. Smith charts 93 located in the lower half of the chart because, in this instance, X is a negative quantity and represents capacitive reactance. Thus, the junction of the R = 1 constant resistance circle and the X = –1 constant reactance circle defines that point. In general, then, to find any series impedance of the form R + jX on a Smith chart, you simply find the junction of the R = constant and X = constant circles. In order to give you a clearer picture of impedance values on the Smith chart, we plot additional impedance values in Figure 3.4. These values are shown in Table 3.1. Table 3.1 Impedance values for points plotted in Figure 3.4 A = 1 + j1 B = 1 – j1 C = 0 + j0 D = 0.2 + j0.2 E = 0.2 + j0.7 F = 0.2 + j1.2 G = 0.5 + j0.5 H = 1 + j0 I = ∞ + j0 J = 6 + j2 K = 0.2 – j0.6 L = 0.5 – j0.2 M = 0.6 – j2 N = 5 – j5 Try to plot these values on Figure 3.4 and check if you get the correct values. In some cases, you will not find the circles that you want; when this happens, you will have to interpolate between the two nearest values that are shown. Hence, plotting imped- ances on the Smith chart produces a plotting error. However, the error introduced is rela- tively small and is negligible for practical work. If you try to plot an impedance of Z = 20 + j20 W, you will not be able to do it accu- rately because the R = 20 and X = 20 W circles would be (if they were drawn) on the extreme right edge of the chart – very close to infinity. In order to facilitate the plotting of larger impedances, normalisation is used. That is, each impedance to be plotted is divided by a convenient number that will place the new normalised impedance near the centre of the chart where increased accuracy in plotting is obtained. For the preceding example, where Z = 20 + j20 W, it would be convenient to divide Z by 100, which yields the value Z = 0.2 + j0.2. This is very easily found on the chart. The important thing to realise is that if normalisation is carried out for one impedance then all impedances plotted on that chart must be divided by the same number in the normalisation process. Otherwise, you will not be able to use the chart. Last but not least, when you have finished with your chart manipulations, you must then re-normalise (multiply by the same number used previously) to get your true values. Example 3.1 Plot the points (0.7 – j0.2), (0.7 + j0.3), (0.3 – j0.5) and (0.3 + j0.3) on the Smith chart in Figure 3.4. Solution. The above points are all shown on the Smith chart in Figure 3.5. Check your plotting points in Figure 3.4 against those in Figure 3.5. 3.2.3 Q of points on a Smith chart Since the quality factor Q is defined as reactance/resistance, it follows that every point on the Smith chart has a value of Q associated with it. For example, the plotted points of Example 3.1 are shown in Table 3.2. 94 Smith charts and scattering parameters Table 3.2 Q values of the points in Example 3.1 Resistance Reactance Q = |X|/R (R) (X) 0.7 –0.2 0.286 0.7 +0.3 0.429 0.3 –0.5 1.667 0.3 +0.3 1.000 At the moment, it is not clear as to what can be done with these Q values but you will understand their validity later when we investigate broadband matching techniques in Section 3.8.2. 3.2.4 Impedance manipulation on the chart Fig. 3.5 A = 0.7 + j0.3, B = 0.7 – j0.2, C = 0.3 – j0.5, D = 0.3 + j0.3 Figure 3.5 indicates graphically what happens when a series capacitive reactance of –j0.5 W is added to an impedance of Z = (0.7 + j0.3) W. Mathematically, the result is Smith charts 95 Z = (0.7 + j0.3 – j0.5) W = (0.7 – j0.2) W which represents a series RC quantity. Graphically, we have plotted (0.7 + j0.3) as point A in Figure 3.5. You then read the reactance scale on the periphery of the chart and move anti-clockwise along the R = 0.7 W constant resistance circle for a distance of X = –j0.5 W. This is the plotted impedance point of Z = (0.7 – j0.2) W, shown as point B in Figure 3.5. Adding a series inductance to a plotted impedance value simply causes a move clock- wise along a constant resistance circle to the new impedance value. Consider the case in Figure 3.5 where a series inductance j0.8 W is added to an impedance of (0.3 – j0.5) W. Mathematically the result is Z = (0.3 – j0.5 + j0.8) W = (0.3 + j0.3) W Graphically, we have plotted point (0.3 – j0.5) in Figure 3.5 as point C then moved along the 0.3 resistance circle and added j0.8 to that point to arrive at point D. In general the addition of a series capacitor to a plotted impedance moves that imped- ance counter-clockwise along a constant resistance circle for a distance that is equal to the reactance of the capacitor. The addition of a series inductor to a plotted impedance moves that impedance clockwise along a constant resistance circle for a distance that is equal to the reactance of the inductor. 3.2.5 Conversion of impedance to admittance The Smith chart, described so far as a family of impedance coordinates, can easily be used to convert any impedance (Z) to an admittance (Y), and vice-versa. In mathematical terms, an admittance is simply the inverse of an impedance, or Y=— (3.1) where, the admittance (Y) contains both a real and an imaginary part, similar to the imped- ance (Z). Thus Y = G ± jB (3.2) G = conductance in Siemens (S) B = susceptance in Siemens (S) To find the inverse of a series impedance of the form Z = R + jX mathematically, you would simply use Equation 3.1 and perform the necessary calculation. But, how can you use the Smith chart to perform the calculation for you without the need for a calculator? The easi- est way of describing the use of the chart in performing this function is to first work a prob- lem out mathematically, and then plot the results on the chart to see how the two functions are related. Take, for example, the series impedance Z = (1 + jl) W. The inverse of Z is Y = ———— = —————— = 0.7071 S ∠ –45° = (0.5 –j0.5) S 1 + j1 W 1.414 W ∠45° If we plot the points (1 + jl) and (0.5 – j0.5) on the Smith chart, we can easily see the graphical relationship between the two. This construction is shown in Figure 3.6. Note that 96 Smith charts and scattering parameters Fig. 3.6 Changing an impedance to admittance: A = (1 + j1) Ω, B = (0.5 – j0.5) S the two points are located at exactly the same distance (d) from the centre of the chart but in opposite directions (180°) from each other. Indeed, the same relationship holds true for any impedance and its inverse. Therefore, without the aid of a calculator, you can find the reciprocal of an impedance or an admittance by simply plotting the point on the chart, measuring the distance (d) from the centre of the chart to that point, and then plotting the measured result the same distance from the centre but in the opposite direction (180°) from the original point. This is a very simple construction technique that can be done in seconds. Example 3.2 Use the Smith chart in Figure 3.6 to find the admittance of the impedance (0.8 – j1.6). Given: Z = (0.8 – j1.6) Required: Admittance value Y Solution. The admittance value is located at the point (0.25 + j0.5). You can verify this yourself by entering the point (0.8 – j1.6) in Figure 3.6. Measure the distance from your The immittance Smith chart 97 point to the chart centre. Call this distance d. Draw a line of length 2d, from your point through the centre of the chart. Read off the coordinates at the end of this line. You should now get (0.25 + j0.5). 3.3 The immittance Smith chart Fig. 3.7 Immittance Smith chart – reading a point as an impedance or admittance Alternatively, we can use another Smith chart, rotate it by 180°, and overlay it on top of a conventional Smith chart. Such an arrangement is shown in Figure 3.7. The chart that you see in Figure 3.7 is one which I have prepared for you. Detailed charts are also obtainable commercially as Smith chart3 Form ZY-01-N. With these charts, we can plot 3 Smith chart Form ZY-01-N is a copyright of Analog Instruments Co, P.O. Box 808, New Providence, NJ 07974, USA. 98 Smith charts and scattering parameters the coordinates (1 + j1) directly on the impedance chart and read its admittance equivalent (0.5 – j0.5) on the rotated admittance chart directly. Another approach that we could take (if we are working solely with admittances) is to just rotate the chart itself 180° and manip- ulate values on the chart as admittances. This will be shown more clearly in the next section. 3.4 Admittance manipulation on the chart Fig. 3.8 Impedance chart used as an admittance chart: A = (0.2 – j0.6) S, B = (0.2 + j0.3) S, C = (1.2 + j0.4) S, D = (1.2 – j0.6) S In this section, we want to present a visual indication of what happens when a shunt element is added to an admittance. The addition of a shunt capacitor is shown in Figure 3.8. For an example we will choose an admittance of Y = (0.2 – j0.6) S and add a shunt capacitor with a susceptance (reciprocal of reactance) of +j0.9 S. Mathematically, we Smith chart theory and applications 99 know that parallel susceptances are simply added together to find the equivalent suscep- tance. When this is done, the result becomes: Y = (0.2 – j0.6) S + j0.9 S = (0.2 + j0.3) S If this point is plotted on the admittance chart, we quickly recognise that all we have done is to move along a constant conductance circle (G) clockwise a distance of jB = 0.9 S. In other words, the real part of the admittance has not changed, only the imaginary part. Similarly, if we had a point (1.2 + j0.4) S and added an inductive susceptance of (–j10) S to it, we would get (1.2 + j0.4) S – j10 S = (1.2 – j0.6) S. This is also shown in Figure 3.8. Hence, adding a shunt inductance to an admittance moves the point along a constant conductance circle counter-clockwise a distance (–jB) equal to the value of its susceptance, –j10 S, as shown in Figure 3.8. 3.5 Smith chart theory and applications This section deals with the derivation of the resistance (R) and reactance (X) circles of the Smith chart (see Figure 3.9). If you are prepared to accept the Smith chart and are not inter- ested in the theory of the chart, then you may ignore all of Section 3.5.1 because it will not stop you from using the chart. 3.5.1 Derivations of circles Our definitions are: (i) the normalised load impedance is Z R + jX z= L = = r + jx Z0 Z0 (ii) the reflection coefficient is G = p + jq (3.4) Here p (for in-phase) is the real part of G and q (for quadrature) is the imaginary part. From Part 2, we use the definition for G = (Z L– Z 0)/(Z L+ Z 0) and changing into normalised values by using Equation 3.3, we obtain z −1 z +1 and by transposing z = —— Substituting z from Equation 3.3 and Γ from Equation 3.4 gives 1 + p + jq r + jx = ———— 1 – p – jq 100 Smith charts and scattering parameters Fig. 3.9 Resistive and reactive circles in the Smith chart To rationalise the denominator, multiply through by [(1 – p) + jq]. This gives [(1 + p) + jq][(1 − p) + jq] r + jx = [(1 − p) − jq][(1 − p) + jq] (1 − p 2 − q 2 ) + j2 q (1 − p)2 + q 2 Equating real parts (1 − p 2 − q 2 ) r= (3.5) (1 − p)2 + q 2 Equating imaginary parts x= (3.6) (1 − p)2 + q 2 Smith chart theory and applications 101 First, we derive the equation of an r circle. From Equation 3.5 r(1 – 2p + p2 + q 2) = (1 – p2 – q 2) (r + 1)p 2 – 2pr + (r + 1)q 2 = 1 – r Dividing throughout by (r + 1) ⎛ p 2 − 2 pr ⎞ + q 2 = 1 − r × (1 + r ) = 1 − r ⎝ r + 1⎠ r + 1 (1 + r ) (r + 1)2 To complete the square in p, add r2/(r + 1)2 to both sides. This gives ⎛ 2 2 pr r2 ⎞ 1 − r2 r2 ⎜ p − r +1 + 2⎟ + q2 = 2 ⎝ (r + 1) ⎠ (r + 1) (r + 1)2 ⎛ p − r ⎞ + q2 = ⎛ 1 ⎞ (3.7) ⎝ r + 1⎠ ⎝ r + 1⎠ This is the equation of a circle, with centre at [p = r/(r +1), q = 0] and radius 1/(r + 1). For any given value of r, the resultant is called a constant-r circle, or just an r circle. Next, we derive an equation of an x circle. From Equation 3.6 x(1 – 2p + p 2 + q 2) = 2q Dividing throughout by x ( p 2 − 2 p + 1) + ⎛ q 2 − ⎞ = 0 ⎝ x⎠ To complete the square, we add 1/x 2 to both sides: ⎛ 2q 1 ⎞ 1 ( p 2 − 2 p + 1) + ⎜ q 2 − + 2⎟ = 2 ⎝ x x ⎠ x ( p − 1)2 + ⎛ q − ⎞ = ⎛ ⎞ ⎝ x⎠ ⎝ x⎠ This is the equation of a circle, with centre at [ p = 1, q = 1/x] and radius, 1/x. For any given value of x, the resultant circle is called a constant-x circle, or just an x circle. 3.5.2 Smith chart applications As the proof and theory of the Smith chart has already been explained in Section 3.5.1, we will now concentrate on using the chart. We will commence by using the chart to find reflection coefficients and impedances of networks, then progress on to using the chart for matching with λ/4 transformers and tuning stubs. 102 Smith charts and scattering parameters 3.6 Reflection coefficients and impedance networks 3.6.1 Reflection coefficients The Smith chart can be used to find the reflection coefficient at any point, in modulus-and- angle form. If we plot the point (0.8 – j1.6) denoted by point A on the Smith chart of Figure 3.10 and extend the line OA to B, we will find by measurement that the angle BOC is about –55.5°. You will not see this angle scale in Figure 3.10 because our condensed Smith chart does not have an angle scale.4 The modulus of the reflection coefficient can be found from Equation 2.38 which states 1 + Γv VSWR = 1 − Γv Fig. 3.10 Reflection coefficient: A = (0.8 – j1.6), angle BOC = –55.5° 4 The full Smith chart also carries an angle scale. See Figure 3.1. Reflection coefficients and impedance networks 103 So, rearranging VSWR − 1 Γv = VSWR + 1 In our example, VSWR5 ≈ 5, so |Γv | ≈ (5 – 1)/(5 + 1) = 0.667 and hence the reflection coef- ficient = 0.667/–55.5°. Some Smith charts such as Figure 3.1 do have ‘radially scaled parameters’ scales, and it is possible to obtain the reflection coefficient magnitude directly by simply measuring the radius of the VSWR circle and reading off the same distance on the voltage reflection coefficient scale. Alternatively, use Equation 2.38a to calculate it. Example 3.3 In Figure 3.11, the VSWR circle has a radius of 0.667. An impedance is shown on the Smith chart as point B which is (0.25 – j0.5). What is its reflection coefficient? Given: VSWR circle radius = 0.667. Impedance at point B = (0.25 – j0.5). Required: Voltage reflection coefficient Γ. Solution. The answer is 0.667 /–124°. This is shown as point C in Figure 3.11. Fig. 3.11 Smith chart for Examples 3.3 and 3.4 5 VSWR is obtained by completing the circle enclosing the point A (Figure 3.10). It is then read off the inter- section between the circle and the real axis and in this case = 5. Proof of this will be given when we derive Equation 3.14. 104 Smith charts and scattering parameters Example 3.4 In Figure 3.11, the VSWR circle has a radius of 0.667. If the angle AOD is +156°, what impedance does the point E represent on the Smith chart? Given: VSWR circle radius = 0.667 AOD = +156°. Required: Impedance at point E. Solution. The answer is approximately 0.21 + j0.21. This is shown as point E in Figure 3.6.2 Impedance of multi-element circuits The impedance and/or admittance of multi-element networks can be found on the Smith chart without any calculations. Example 3.5 What is (a) the impedance and (b) the reflection coefficient looking into the network shown in Figure 3.12? Given: Network shown in Figure 3.12. Required: (a) Input impedance, (b) reflection coefficient. Fig. 3.12 Network to be analysed Fig. 3.13 Circuit of Figure 3.12 dis-assembled for analysis Reflection coefficients and impedance networks 105 Solution. The problem is easily handled on a Smith chart and not a single calculation needs to be performed. The solution is shown by using Figure 3.13. (a) To find the impedance, proceed as follows. (1) Separate the circuit down into individual branches as shown in Figure 3.13. Plot the series branch where Z = (1 + j1.2) W. This is point A in Figures 3.13 and (2) Add each component back into the circuit – one at a time. The following rule is particularly important. Every time you add an impedance, use the impedance part of the chart. Every time you add an admittance, use the admittance part of the chart. If you observe the above rule, you will have no difficulty following the construction order below: Fig. 3.14 Plot of Example 3.5: A = (1 + j1.2 ) Ω or (0.41 – j0.492) S, B = (0.3 + j0.8) Ω or (0.41 – j1.092) S, C = (0.3 – j0.2) Ω or (2.3326 + j1.522) S, D = (0.206 – j0.215) Ω or (2.326 + j2.422) S, E = (0.206 + j0.635) Ω or (0.462 – j1.425) S, F = 0.746 ∠ 113.58° 106 Smith charts and scattering parameters Arc AB = shunt L = – jB = –0.6 S Arc BC = series C = –jX = –1.0 Ω Arc CD = shunt L = +jB = +0.9 S Arc DE = series C = +jX = +0.85 Ω (3) The impedance value (point E) can then be read directly from Figure 3.14. It is Z = (0.2 + j0.63). (b) To find the reflection coefficient, proceed as follows. (1) Draw a line from the centre of the chart (Figure 3.14) through the point E to cut the chart periphery at point F. Measure the distance from the chart centre O to point E and transfer this distance to the reflection coefficient scale (if you have one) to obtain its value.6 This value is 0.74. (2) Read the angle of intersection of the line OE and the periphery. This angle is 114°. (3) Hence the value of the reflection coefficient is 0.74 ∠114°. 3.7 Impedance of distributed circuits In the previous example, we showed you how the Smith chart can be used for lumped circuit elements. In Sections 3.7 and 3.8, we will show you how the Smith chart can also be used with distributed circuit elements like transmission lines. For ease of verifying Smith chart results, some of the transmission line expressions derived earlier will now be repeated without proof. These are: ⎡1 + Γv e −2γl ⎤ Zl = Z 0 ⎢ −2γl ⎥ (3.9) ⎣1 − Γv e ⎢ ⎥ For a lossless line, with g = jb, this becomes ⎡1 + Γv e − j2 βl ⎤ Zl = Z 0 ⎢ − j2 βl ⎥ ⎣1 − Γv e ⎢ ⎥ Equation 3.9 has been shown to be ⎡ Z sinh γl + ZL cosh γl ⎤ (3.11) Zin = Z0 ⎢ 0 ⎥ ⎣ Z0 cosh γl + ZL sinh γl ⎦ Equation 3.11 can also be written in the form Zin ⎡ Z0 sinh γl + ZL cosh γl ⎤ =⎢ ⎥ (3.12) Z0 ⎣ Z0 cosh γl + ZL sinh γl ⎦ It is also possible to divide each term in Equation 3.12 by (Z 0 cosh gl) and, remembering that for a lossless line that tanh gl = j tan bl, we get 6 The unfortunate part of this condensed Smith chart is that we do not have a voltage reflection coefficient scale. So please accept my answer for now until we use PUFF. Alternatively, use Equation 2.38a to calculate it. Impedance of distributed circuits 107 Zin ⎡ j tan βl + ZL Z0 ⎤ =⎢ ⎥ (3.13) Z0 ⎣ j ( ZL Z0 ) tan βl + 1 ⎦ Note Equations 3.12 and 3.13 have been normalised with respect to Z 0. Although stated earlier, we will re-iterate that normalisation is used on Smith charts because it enables a larger range of values to be covered with greater accuracy on the same chart. However, if we divide a value by Z 0 (normalised) before entering it on the Smith chart, it stands to reason that we must then multiply the Smith chart result by Z 0 (re-normalised) to gets its true value. Nowadays, the above mathematical calculations can be easily programmed into a computer, and you may well question the necessity of the Smith chart for line calculations. However, as you will see shortly the Smith chart is more than just a tool for line calcula- tions; it is invaluable for gaining an insight into line conditions for matching purposes, parameter presentation, constant gain circles, stability and instability circles, Qs of elements, standing-wave ratios, and voltage maxima and minima positions. The input and output impedances of transistors are usually complex, with a significant reactive component. The Smith chart is particularly useful for matching purposes when a transmission line is terminated by the input of a transistor amplifier, or when the line is driven from an amplifier. Matching is necessary because it avoids reflections on the lines and ensures maximum power transfer from source to load. 3.7.1 Finding line impedances Smith charts can be used to find line impedances as demonstrated by the following ex- Example 3.6 A transmission line with a characteristic impedance Z 0 = 50 Ω is terminated with a load impedance of Z L = (40 – j80) Ω. What is its input impedance when the line is (a) 0.096λ, (b) 0.173λ and (c) 0.206λ? Given: Z 0 = 50 Ω, Z L = (40 – j80) Ω. Required: The input impedance Z in of the terminated line when (a) the line is 0.096λ, (b) 0.173λ and (c) 0.206λ . Solution. First, the load impedance is expressed in normalised form as ZL ( 40 − j80)Ω = = 0.8 − j1.6 Z0 50Ω This value is plotted on the chart as point A in Figure 3.15. Note that this point is the inter- section of the arcs of two circles. The first is that which cuts the horizontal axis labelled ‘resistance component (R/Z 0)’ at the value 0.8. Because the reactive component is nega- tive, the second circle is that which cuts the circular axis on the periphery labelled ‘capac- itance reactance component (–jX/Z 0)’ at the value 1.6. A line is now drawn from the centre of the Smith chart (point 1 + j0) through the point 0.8 – j1.6 and projected to the periph- ery of the circle to cut the ‘wavelengths towards generator’ circle at 0.327l. This is shown as point B. 108 Smith charts and scattering parameters Fig. 3.15 Finding input impedance of a line: A = 0.8 – j1.6, B = 0.327l, C = 0.423l, D = 0.25 – j0.5 E = 0.5l, or 0l, F = 0.2 + j0, G = 0.033l, H = 0.2 + j02, I = 0.077l, J = 0.25 – j0.5, K = 5 + j0 Next, a circle is drawn with its centre at the centre of the chart (point 1 + j0), passing through the load impedance value (point A) in Figure 3.15. This circle represents all possi- ble line impedances along the transmission line and we will call it our impedance circle.7 (a) We wish to know Z in when the TX line is 0.096l long. For this, we start at the point B, 0.327l on the ‘wavelengths towards generator’ circle and move 0.096l in the direc- tion of the generator (i.e. away from the load). Since 0.327l + 0.096l = 0.423l, the point we want is 0.423l on the ‘wavelengths towards generator’ circle. I have denoted this point as point C. From C, draw a straight line to the Smith chart centre. Where this line cuts our impedance circle, read out the value at the intersection. I read it as (0.25 – j0.5) and have marked it as point D. To get the actual value, I must re-normalise the chart value by 50 W and get (0.25 – j0.5) × 50 W = (12.5 – j25) W. 7 This circle is also called the voltage standing wave ratio (VSWR) circle. Impedance of distributed circuits 109 (b) For the case where the line length is 0.173l, I must move 0.173l on the ‘towards the generator’ scale from the same starting point of 0.327l, i.e. point B. So I must get to the point (0.327 + 0.173)l or 0.5l on the ‘wavelengths towards generator’ scale. This is shown as point E in Figure 3.15. Joining point E with the Smith chart centre shows that I cut our original impedance circle at the point F, where the value is (0.2 + j0). To get the true value, I must re-normalise, (0.2 + j0) × 50 W = (10 + j0) W. Note: It is possible to get a pure resistance from a complex load by choosing the right length of transmission line. This is very important as you will see later when we do designs on matching complex transistor loads to pure resistances. (c) For the case where the line length is 0.206l, I must move 0.206l on the ‘towards the generator’ scale from the same starting point of 0.327λ, i.e. point B. This scale only goes up to 0.5l and then restarts again. So I must get to 0.5l which is a movement of (0.5 – 0.327)l or 0.173l then add another (0.206 – 0.173)λ or 0.033l to complete the full movement of 0.206l to arrive at point G. Joining point G with the Smith chart centre shows that I cut our original impedance circle at the point H, where the value is (0.2 + j0.2). To get the true value, I must re-normalise, (0.2 + j0.2) × 50 W = (10 + j10) W. If you wish, you may confirm these three values (12.5 – j25) W, 10 W and (10 + j10) W by calculations using Equation 3.11 but bear in mind that you will have to change the wave- length8 into radians before applying the equation. Example 3.7 Show that, when Z L = R L + j0 on a lossless line, the VSWR equals R L/Z 0. (Hint: First find the reflection coefficient of the load.) Solution. Using Equation 2.28 ZL – Z0 Γv = ———— ZL + Z0 When Z L = R L, this becomes RL – Z0 Γv = ———— RL + Z0 Here, both R L and Z 0 are purely resistive, so Γv is a real number. Using Equation 1 + Γv 1 + Γv VSWR = = 1 − Γv 1 − Γv because Γv is real. So 8 One wavelength = 2π radians. 110 Smith charts and scattering parameters 1 + (R L − Z0 ) ( RL + Z0 ) VSWR = 1 − ( RL − Z0 ) ( RL + Z0 ) ( RL + Z0 ) + ( RL − Z0 ) ( RL + Z0 ) − ( RL − Z0 ) 2 RL 2 Z0 VSWR = (3.14) It has been shown in Example 3.7 that when Z L = R L, and Z 0 is resistive, the VSWR is given simply by VSWR = R L/Z 0. In this case R L/Z 0 = 5.0 (point K in Figure 3.15), so the VSWR is 5.0. Thus the point where the circle cuts the right-hand horizontal axis gives the VSWR on the line. Looking at successive points around the standing-wave circle drawn through the load impedance is equivalent to looking at successive points along a lossless line on which the VSWR equals that of the circle. The successive values of input line impedances at points D, F, H, K around the circle correspond to line impedances at successive points along the line. The distance along the line is directly proportional to the angle around the standing-wave circle. One complete revolution takes us from a voltage minimum at the point F in Figure 3.15, where Z in = 0.2 Z 0, to the point opposite this on the circle with a voltage maximum where Z in = 5 Z 0 at point K, and back to the first minimum. Since standing-wave minima repeat every half wavelength, one complete revolution corresponds to λ /2. The peripheral scales marked ‘wavelengths towards generator’ and ‘wavelengths towards load’ are calibrated accordingly. Figure 3.15 shows that, for our example, the position (point F) of the first voltage mini- mum is at 0.173λ back from the load, clockwise around the scale ‘wavelengths toward generator’. The first maximum (point K) is shown at [(0.5 – 0.327) + 0.25]λ or 0.423λ from the load, clockwise around the ‘wavelengths towards generator’ scale. The distance between voltage maxima and minima is 0.25λ as you should expect from transmission line theory. Example 3.8 Use the Smith chart in Figure 3.15 to find the line impedance at a point one quarter wave- length from a load of (40 – j80) Ω. Given: ZL = (40 – j80)Ω, l = λ/4. Required: Z @ λ/4 from ZL. Solution. Moving around the chart away from the load and towards the generator (that is clockwise) through 0.25l (that is 180°) brings us to the normalised impedance (0.25 + j0.5), point J in Figure 3.15. Since the chart was normalised to 50 Ω, to get the true value we must multiply (0.25 + j0.5) × 50 = (12.5 + j25) Ω. 3.8 Impedance matching When a load such as a transistor input, with a substantial reactive component, is driven from a transmission line, it is necessary to match the load to the line to avoid reflections and to Impedance matching 111 transfer the most power from source to load. The reactive component of the load can be tuned out, and the resistive component matched to the line, using a matching network of inductors and capacitors. However, at UHF and microwave frequencies, lumped inductors and capacitors can be very lossy, and much higher Q values can be obtained by using addi- tional sections of transmission line instead. There are two common techniques used, the quarter-wavelength transformer and the stub tuner. These are described below. 3.8.1 Impedance matching using a λ/4 transformer This is shown by Example 3.9 which first uses a line length to convert a complex load to a resistive load and then uses a 1/4 line transformer to transform the resistive load to match the desired source impedance. Example 3.9 Figure 3.15 shows how a quarter-wavelength section of line can be used to match a load, such as the input of a transistor, to a line. Suppose the load has the normalised value of the previ- ous example, that is (0.8 – j1.6), point A in Figure 3.15. First, the Smith chart is used to choose a length l of line which, when connected to the load, will have a purely resistive input imped- ance. In this example, the length could be either 0.173λ, with a normalised input impedance of 0.2 (point F in Figure 3.15) or 0.432λ with a normalised input impedance of 5.0 (point K in Figure 3.15). Suppose we choose the higher value, with l = 0.432λ and Z /Z 0 = 5.0. Next, we calculate the characteristic impedance of the quarter-wave section. It is required to match Z in to the input line which is Z 0, so its input impedance Z in must equal Z 0. The λ/4 transformer. The equation for a quarter-wave transformer has been derived in Chapter 2 as Equation 2.57. To distinguish the main transmission line impedance (Z 0) from the λ/4 transformer line impedance, we shall denote the latter as Z 0t. Therefore Z0 t Zin = or Z0 t = Zin ZL Since we wish to make Z in of the l/4 transformer match Z 0, we therefore get Z0 t = Zin ZL = Z0 ZL Normalising, this becomes Z0 t Z0 Z L ZL = = Z0 Z0 Z0 In the example, Z L/Z 0 = 5.0. Therefore Z0 t = 5.0 ≈ 2.24 Therefore, the λ/4 transformer characteristic impedance, Z 0t = 2.24 Z 0. With Z 0 = 50 Ω Z 0t = 2.24 × 50 Ω ≈ 112 Ω In microstrip, an impedance of 112 Ω is possible but the microstrip itself is beginning to get narrow and fabrication accuracy of the 112 Ω line might be more difficult. 112 Smith charts and scattering parameters Example 3.10 Find the characteristic impedance Z 0t of a λ/4 transformer required for the case when Z L/Z 0 = 0.2, and Z 0 = 50 Ω. Solution. Again using Equation 2.57 Z0 t Z0 = ZL Z0 = 0.2 = 0.447 So, with Z 0 = 50 Ω Z 0t = 0.447 × 50 ≈ 22 Ω The answer to Example 3.7 shows that the required λ/4 line’s characteristic impedance turns out to be low. In microstrip, a low line impedance means that the microstrip itself is wider and in some cases this might be an easier fabrication process. In general, a higher value of Z 0t results if a λ/4 transformer is coupled to a standing- wave voltage maxima on the matching line, and a lower value of Z 0t results if a λ/4 trans- former is coupled to a standing-wave voltage minima on the matching line. The choice as to where the λ/4 transformer is coupled will depend on circumstances such as physical size, dielectric constants of microstrip line, etc. 3.8.2 Broadband matching using λ/4 transformers Broadband matching is used when we want to achieve the best compromise match between source and load across a given bandwidth. Compromise is necessary because perfect matching at all individual frequencies is not feasible. The term ‘broadband’ implies that impedance compensation should be achieved over frequency ranges larger than 50% of the central frequency. Distributed elements, due to their fixed geometric characteristics, are usually poor performers when broadband performance is required. There are, nevertheless, distributed networks that exhibit better broadband performance than others. For example, the λ/4 line transformer of Figure 3.16(a) allows matching over a small frequency band, while two λ/4 lines in cascade (Figure 3.16(b)) provide a greater matching bandwidth and, of course, the Fig. 3.16 Layout of line transformers: (a) one l/4; (b) two l/4 lines in cascade; (c) five l/4 lines cascaded Impedance matching 113 Fig. 3.17 Constant-Q arcs on the Smith chart five λ/4 cascaded transformers of Figure 3.16(c) would provide an even greater bandwidth. In general cascading more quarter-wave transformers provides greater bandwidth. However, you should be aware that λ/4 line transformers can only be used in the GHz range because below these frequencies λ/4 lengths can be very long. For example at 30 MHz in air, λ/4 = 2.5 m. When quarter-wave length lines are required at low frequencies, the lumped circuit equivalent of a quarter-wave line length (often a π circuit) is used. In the next example, we will investigate the difference in bandwidth obtained between using a single λ/4 transformer and a transformer produced by two λ/4 lines in cascade. However, before commencing, it is worth investigating how the Smith chart can be used to help design. In Section 3.2.3, we showed that any point on the Smith chart has a Q value asso- ciated with it. The locus of impedances on the chart with the same Q is an arc that crosses the open-circuit and short-circuit loads. Several Q arcs are shown in Figure 3.17. The Q arcs in the Smith chart can be used to provide the limits within which the matching network should remain in order to provide a larger operational bandwidth. Remembering that Q = fcentre/fband- width, it follows that for a given centre frequency a wider bandwidth requires a lower Q. Example 3.11 A source impedance Z S of (50 + j0) is to be matched to a load of (100 + j0) over a frequency range of 600–1400 MHz. Match the source and load by using (a) one 114 Smith charts and scattering parameters quarter-wave transformer and (b) two quarter-wave transformers. (c) Sketch a graph of the reflection coefficient against frequency. Given: Z S = (50 + j0) Ω, Z L = (100 + j0) Ω, bandwidth = 600–1400 MHz. Required: (a) Matching network using one λ/4 transformer, (b) matching network using two λ/4 transformers, (c) a sketch of their network reflection coefficient against bandwidth. (a) Use one quarter-wave transformer as in the circuit of Figure 3.16(a). We start by using Equation 2.57 which is Z in = Z 02/Z L which yields Z0 = Zin ZL = (50 + j0)(100 + j0) = 70.71Ω (b) Use two quarter-wave transformers as in Figure 3.18. Note in this case, I have called the characteristic impedance of the first λ /4 line from the load, Z 0t1 and the character- istic impedance of the second λ /4 line from the load, Z 0t2. Fig. 3.18 Matching with two quarter-wave transformers From Equation 2.57 Z A = (Z 0t1) 2/Z L Again using Equation 2.57, and substituting for ZA Z in = (Z 0t2) 2/ZA = (Z 0t2) 2/(Z 0t1)2/Z L Sorting out, we get Zin ( Z0 t2 )2 Z0 t1 ZL = or = ZL ( Z0 t1 )2 Z0 t2 Zin Bearing in mind that Z in must match the Z s and substituting in values Z0 t1 100 + j0 = = 1.414 Z0 t2 50 + j0 If I choose a value of 60 Ω for Z 0t2 then Z 0t1 = 1.414 × 60 = 84.85 Ω (c) If the reflection coefficients of the network 1 and network 2 are plotted against frequency, you will get Figure 3.19. I have also included Table 3.3 to give you some idea of the difference between the networks. From both the table and the graph, you should note that the two λ/4 network has lowered the reflection coefficient by approx- imately 6 dB at 600 MHz and 1400 MHz. There has also been a reduction of about 12.8 dB at 800 MHz and 1200 MHz. Impedance matching 115 Fig. 3.19 Matching with λ/4 line transformers: using one l/4 transformer; using two l/4 transformers Table 3.3 Reflection coefficient (dB) against frequency (GHz) (GHz) 0.6 0.8 1.0 1.2 1.4 One l/4 TX –13.83 –19.28 > –60 –19.28 –13.83 Two l/4 TXs –18.81 –32.09 –38.69 –32.09 –18.81 Note: The Smith chart graphics and calculations to obtain this graph are quite long; to save work, I have used the PUFF software supplied with this book. 3.8.3 Impedance matching using a stub tuner An alternative method to impedance matching by λ/4 transformers is shown in Figure 3.20 where a transmission line stub (stub matching) is tapped into the main transmission line R 0 at a distance l 1 from the load Z L to provide a good match between Z L and a source Fig. 3.20 Principle of stub matching 116 Smith charts and scattering parameters generator, R 0. The process appears simple enough but the line length l 1 and the stub length are critical and must be carefully controlled for a good match. There are several methods of calculating these line lengths and we will give you two methods at this stage. These are explained and illustrated in Tables 3.4 and 3.5 . Examples of how these methods are used in calculating line lengths are given in Example 3.11 which follows after the explanation. Example 3.12 is an example of how stub matching is carried out on a Smith Table 3.4 (Matching method 1) Step 1 Z L is the load which is to be matched to the transmission line, R 0 , and its generator, R 0 for maximum power transfer and a good match. Line l1 is the line length which will be used to trans- form the load to the plane AA′. Step 2 Convert the load Z L into its admittance form, i.e. conductance G L and susceptance B L. Step 3 Transform via line length l1, conductance G L and susceptance B L to G L′ and B L′. Choose line length l1 so that G L′ = 1/R 0, i.e. 1 on the conduc- tance circle. Ignore the reactive component B L′ for the time being. Step 4 Introduce a reactive conjugate component (B L′)* to tune out B L′. The net result is that they cancel out the effect of each other. Step 5 Since the effects of the reactive elements have been cancelled, the net result is a conductance G L′. Step 6 This figure results when G L′ is mathematically transformed back to R 0 . We now have a good matched system for maximum power transfer. Impedance matching 117 Table 3.5 (Matching method 2) Step 1 Z L is the load which is to be matched to the transmission line, R 0 , and its generator, R 0 for maximum power transfer and a good match. Line l1 is the line length which will be used to trans- form Z L to the plane AA′. Step 2 At plane AA′, the load Z L has been transformed via line length l1 to Z L′. Step 3 Z L′ has been converted into G L′ and B L′. Choose line length l1 so that G L′ = 1/R 0 . Ignore the reac- tive component B L′ for the time being. Step 4 A reactive conjugate component (B L′)* is now introduced to tune out B L′. The total effect of these reactive elements is that they ‘cancel out’ the effect of each other. Step 5 Since the effects of the reactive elements have cancelled each other out, the circuit is terminated in a conductance G L′. Step 6 This figure results when G L′ is mathematically transformed back to R 0 . We now have a good matched system for maximum power transfer. Example 3.12 A series impedance load (40 – j80) W is to be matched to a generator source of 50 W via a 50 W transmission line. Design a single stub matching system to provide this result. Given: Z L = (40 – j80) Ω, Z g = 50 Ω, Z 0 = 50 Ω. Required: A single stub matching system. Solution. Two methods will be given. Method 1 is depicted in Figure 3.21 and Method 2 is shown in Figure 3.22. 118 Smith charts and scattering parameters Fig. 3.21 Using matching method 1: A = (0.25 + j0.50) Ω , B = 0.077072λ, C = (1 + j1.8027) S, D = 0.183377λ, E = (∞ + j ∞) S, G = (0 – j1.8027) S, arc BD = 0.106 305l, arc FH = 0.080 606l Method 1 based on Table 3.4. To simplify this example, I will use an ordinary Smith chart in its admittance form. 1 Normalise the load impedance with respect to 50 Ω. This gives (40 – j80)/50 = 0.8 – j1.6. (See step 1 of Table 3.4.) 2 Convert the normalised impedance into its admittance form by calculation. This gives 1/(0.8 – j1.6) = 0.25 + j0.5. (See step 2 of Table 3.4). The value 0.25 + j0.5 is shown as point A in Figure 3.21. Draw a constant SWR circle, using the centre of the Smith chart (point O) and a radius equal to OA. 3 Project the line from the centre of the Smith chart (point O), through point A to point B. Read point B on the ‘wavelengths towards generator’ scale. This is 0.077λ. 4 Transform point A along the SWR circle in the ‘towards generator’ direction until you obtain a conductance of 1 or unity. (Step 3 of Table 3.4.) This is shown as point C in Figure 3.21. At point C, the admittance is (1 + j1.8) S. This tells you that the Impedance matching 119 conductance of the circle is matched but that you must get rid of a susceptance of 5 Project the line OC to point D. Read this value on the wavelength towards generator scale. It is 0.183λ. Subtract this value from the value at point B, i.e. (0.183 – 0.077) λ = 0.106λ. This is the length of the line l1. 6 The unwanted susceptance of +j1.8 obtained in step 4 above must be cancelled out. For this, we must introduce a susceptance of –j1.8 to tune out the unwanted susceptance of +j1.8. (See step 4 of Table 3.4.) Bear in mind that a short circuit (0 Ω) has a conduc- tance of ∞ Ω. We start at point E and increase the stub length until we obtain a suscep- tance of –j1.8. This is point G in Figure 3.21. 7 Project line OG to H and line OE to F. Measure the wavelength distance on the ‘towards generator scale’ between the points F and H to obtain the length of the stub. In this case, it is 0.331 λ – 0.250λ = 0.081λ. Hence the length of the short-circuited tuning stub to produce a susceptance of – j1.8 to cancel out the unwanted +j1.8 is 0.081λ. (See steps 5 and 6 of Table 3.4.) The generator, line and load are now all matched to each other. Results using method 1 • The position of the stub l 1 from the load is 0.106λ. • The length of the short-circuited stub line is 0.081λ. These results are obtained from the chart. Just to convince you that the graphical method is correct, I have also calculated out all the values to several decimal points by using a spreadsheet. These numbers are given in the caption in Figure 3.21; however, you should be aware that in practice, accuracy beyond two decimal points is seldom necessary. In other words, the accuracy of the Smith chart is sufficient for practical design. Method 2 based on Table 3.5. To simplify this example, we will use Smith chart type ZY- 01-N which was first introduced to you in Figure 3.7. This chart is used because it affords easy conversion from impedance to admittance plots and vice-versa. If you have forgotten how to use this chart refer back to Figure 3.7. 1 Normalising Z L with respect to 50 Ω gives (40 – j80)/50 = 0.8 – j1.6. Since this value is impedance, the solid coordinate (impedance) lines are used to locate the point in Figure 3.22. This is plotted as point A in the figure. (See step 1 of Table 3.5.) Extend the line OA to the outer periphery (point B). Note the reading on the ‘wavelengths towards generator scale’. This is 0.327λ and is denoted by point B. 2 Draw a constant SWR circle with its centre at the Smith chart centre (point O) and a radius equal to the distance from the chart centre to point A. 3 Move clockwise (towards the generator) along the constant SWR circle until you come to the unity conductance circle (admittance coordinates) at point C. The reason why point C is chosen is because at the unity conductance circle, the conductance element is matched to the system. (See step 2 of Table 3.5.) Draw a line from the Smith chart centre (point O) through point C to the same ‘wavelengths scale’. This line cuts the circle (point D) at 0.433λ. Subtracting the wavelength value of D from C (0.433–0.327)λ = 0.106λ. This distance is designated as ‘length l 1’ in Figure 3.20. It tells you that the stub must be placed at a point 0.106λ from the load. 120 Smith charts and scattering parameters Fig. 3.22 Using matching method 2 4 Return to point C and read its admittance value which is (1 + j1.8). The conductance value is 1 and it is telling you that at this point the transformed conductive element is already matched to Yo. (See step 3 of Table 3.5.) However, at point C, we also have a susceptance of +j1.8. We want only a conductance element and do not want any suscep- tance and will nullify the unwanted susceptance effect by tuning it out with –j1.8 from the stub line. (See steps 4, 5 and 6 of Table 3.5.) 5 The stub line used in Figure 3.20 is a short-circuit line which means that Z L = 0 + j0 and that its admittance load is (∞ – j∞ ). This is shown as point E on the admittance scale in Figure 3.22. The extended line OE also cuts the ‘wavelengths towards generator’ circle at 0.00λ (point F). We now have to move clockwise (towards the generator away from the short-circuit load) until we generate a susceptance of –j1.8. This is shown as point G in Figure 3.22. The extended line OH from the Smith chart centre through the –j1.8 point is 0.081λ. Therefore the stub length is (0.081 – 0.00)λ = 0.081λ. The gener- ator, line and load are now all matched to each other. Results using method 2 • The position of the stub from the load is 0.106λ. • The length of the short-circuited stub line is 0.081λ. Impedance matching 121 Summing up. Within the limits of graphical accuracy, both methods produce the same • The position of the stub from the load is 0.106λ. • The length of the short-circuited stub line is 0.081λ. Example 3.13 A transistor amplifier has an input resistance of 100 Ω shunted by a capacitance of 5 pF. Find (a) the position of short-circuit stub on the line required to match the amplifier input to a 50 Ω line at 1 GHz and (b) its length. Given: Transistor input impedance = 100 Ω shunted by 5 pF, frequency = 1 GHz. Required: Matching circuit to a 50 Ω line (a) determine length of short-circuit stub, (b) determine its position from the load. Fig. 3.23 Matching of transistor input impedance: A (0.5 + j1.57), B (0.165l), C (1 + j2.3), D (0.193l), E (–j2.3), F (0.315l), G (0.25l) 122 Smith charts and scattering parameters (a) Yo = 1/50 W = 20 mS YL = GL + jwCL = 1/100 W + j2p × 1 GHz × 5 pF = 10 mS + j31.4 mS YL/Yo = 0.5 + j1.57 This is plotted in Figure 3.23 as point A. The radius through this cuts the ‘wavelengths towards generator’ scale at 0.165λ (point B). The VSWR circle cuts the G/Yo = 1 circle at 1 + j2.3 (point C), which corresponds to 0.193λ (point D) toward the generator. So the stub connection point should be at (0.193λ – 0.165)λ = 0.028λ from the transistor input. (b) The required normalised stub susceptance is –j2.3. This is plotted as point E. The radius through this cuts the ‘wavelengths towards generator’ scale at 0.315λ (point F). The short-circuit stub length should be 0.315λ – 0.25λ = 0.065λ. Summing up • The stub connection point is 0.028λ from the transistor input. • The short-circuit stub length is 0.065λ at the connection point. The program PUFF issued with this book has facilities for single stub matching. 3.8.4 Impedance matching using multiple stubs In single stub matching (Figure 3.20) the distance from the load to the stub and the length of the stub must be accurately controlled. In some situations, for example an antenna mounted on a tower, you cannot easily control the distance from antenna to stub, therefore we add one or more stubs to provide matching. One arrangement of double stub matching is shown in Figure 3.24. Fig. 3.24 Double stub matching network Impedance matching 123 In double stub impedance matching, two stubs are shunted at fixed positions across the main transmission line. Each stub may be either short-circuited or open-circuited. Its lengths are given by l1 and l2 respectively. The distance, d2, between the stubs is usually fixed at 1/8, 3/8, or 5/8 of a wavelength, whereas the position of the nearest stub from the load, d1, is determined by the distance from the load. Explanation is best given by an example. Example 3.14 A system similar to that shown in Figure 3.24 has a load Z L = (50 + j50) Ω which is to be matched to a transmission line and source system with a characteristic impedance of 50 Ω. The distance, d1, between the load and the first stub is 0.2λ at the operating frequency. The distance, d2, between the two stubs is 0.125λ at the operating frequency. Use a Smith chart to estimate the lengths of l1 and l 2 of the stubs. Solution. This problem will be solved by normalising all values in the question by 50 W. Hence (50 + j50) Ω and 50 Ω will become (1 + j1) n and 1 n respectively; the ‘n’ is used to denote normalised values. Values will then be plotted on the immittance Smith chart of Figure 3.25 and the chart result will be re-normalised to produce the correct answer. Fig. 3.25 Double stub matching: A = (1 + j1) n, Arc BC = 0.2l, D = (0.759 – j0.838) n, E = (1.653 – j0.224) n, Arc FG = 0.125l, H = (0.781 – j0.421) n, O = (1.008 – j0.001) n 124 Smith charts and scattering parameters Before starting, you should realise that distance d1 and d 2 are out of your control; d1 is fixed by the system structure, d2 is fixed after you have selected your double tuning stub device which is 0.125λ in this case. You can only vary the susceptance of the stubs. Therefore, you vary stub 1 to a convenient point E in Figure 3.25 so that when that value is moved distance d 2 (0.125λ), the new point will be on the unit conductance circle where you can use stub 2 to vary the susceptance value until it reaches the impedance (1 + j0) n. 1 The load is plotted at (1 + j1) using the impedance coordinates. This is shown as A in Figure 3.25. Project OA until it cuts the wavelengths to generator scale at point B which reads 0.161λ. Move along this scale for 0.2λ. This is denoted by the arc BC. Point C is 0.361λ. Draw a line from C to O. 2 An arc of a constant |Γ| circle with radius OA is drawn clockwise from the load point A to D which cuts the line OC. Point D is the value of the transferred load through 0.2λ. From point D, the first susceptance stub moves the transferred load to E. Point E was found experimentally by altering the length of stub 1. Extend line OE to F on the periph- ery. Move the arc along a periphery distance of 0.125λ to G. Arc FG represents the 0.125λ distance between the two stubs. Join O to G. 3 An arc of a constant |Γ| circle with radius OE is drawn clockwise until it cuts the line OG at H. Point H is the transferred load from E after moving through 0.125λ. Ideally, point H should be on the unit conductance circle which means that the resistive element is matched and that stub 2 can now be used to move point H to point O which is the desired point (1 + j0). 4 The normalised values of all the points are given in the annotation for Figure 3.25. From these values, we can now calculate the susceptance which each stub must provide. As before, for stub 1, we need (–j0.1 at E) – (–j0.65 at D) = +j0.55. The length l1 of the stub is found by plotting its load impedance at the point S and following round the ‘wavelengths towards generator’ scale to the point where the 0.55 susceptance circle cuts the perimeter, at about 0.17λ. (The calculated value is 0.167λ.) For stub 2, we need (j0 at O) – (–j0.55 at H) = +j0.55. The length l2 of this stub is found as for stub 1 yielding, again, a value of about 0.17λ. (The calculated value is 0.172λ.) Finally when you are faced with trial and error methods such as selecting point E in the above example, it is much easier if you have a dynamic impedance matching computer program. One such program is the Motorola Impedance Matching Program often called MIMP. This program allows you to alter values and see results instantaneously. MIMP has been written by Dan Moline and at the time of writing this book, Motorola generally issues a copy of it free of charge to bona fide engineers. The program PUFF issued with this book has facilities for checking multiple stub matching. In fact, Example 3.14 is repeated electronically in Secton 4.13.4. Scattering parameters (s-parameters) 125 3.9 Summary of Smith charts The Smith chart is a phasor diagram of the reflection coefficient, Γ, on which constant-r and constant-x circles are drawn, where r and x are the normalised values of the series resistive and reactive parts of the load impedance. The horizontal and vertical axes of the chart are the real and imaginary axes of the reflection coefficient, but they are not labelled as such. Any circle centred on the Smith chart centre is a constant-|Γ| circle and a constant VSWR circle, too. A load impedance, or the impedance looking into a line towards the load, is represented by the intersection of an r circle and an x circle. If a series lumped reactance is added to the load, the r circle through the load imped- ance point is followed and the added normalised reactance is represented by the increase or decrease in the corresponding value of the x circle crossed. If a series line is added at any point then a constant-|Γ| circle is followed, clockwise ‘towards the generator’ through an angle on the chart corresponding to its length in wave- The admittance chart is a version of the impedance Smith chart rotated through 180°. The r and x circles become g and b circles and their intersections represent admittances. The immittance chart is a combination of both the impedance chart and the admittance If a lumped susceptance is shunted across the load, the g circle through the load admit- tance point is followed and the added normalised susceptance is represented by the increase or decrease in the corresponding value of the b circle crossed. If a short-circuited shunt line (stub) is shunted across the line at any point, then the g circle through the point is followed, through a susceptance change corresponding to the stub length in wavelengths. For lengths less than a quarter wavelength, the short- circuit stub appears capacitive and rotation is clockwise round the g circle. For lengths up to three-quarters of a wavelength, the stub appears inductive and rotation is Open-circuit stubs have the opposite susceptance, with rotation in the opposite direc- tion around the g circle. Double stubs are useful when loads are variable. Usually the stub spacing is kept fixed, but the stub lengths are adjustable to achieve matching. 3.10 Scattering parameters (s-parameters) 3.10.1 Introduction Voltages and currents are difficult to measure in microwave structures because they are distributed values and vary with their position in microwave structures. In fact, the widely spread current in a waveguide is virtually impossible to measure directly. Waves are more easily measured in microwave networks. One method of describing the behaviour of a two port network is in terms of incident and reflected waves. This is shown 126 Smith charts and scattering parameters in Figure 3.26. This method is known as scattering parameters or usually denoted as s- parameters. The s-parameter approach avoids many voltage and current problems particu- larly in the measurement of transistors where short- and open-circuit terminations can cause transistor instability and in some cases failure. In many cases, measurement is carried out in s-parameters using an automated computer corrected network analyser. This method is fast and accurate and the results obtained are then mathematically converted into the requisite z, h, y and ABCD parameters. The converted information can be trusted because the accuracy of the original measured data is high. v1 v2 Fig. 3.26 Two port scattering network with source and load 3.10.2 Overall view of scattering parameters Figure 3.26 represents a scattering parameter two-port network driven from a source with impedance Z 0, and driving a load of impedance Z L. In the figure, a1 and a2 represent inci- dent voltage waves; and b1 and b2 represent reflected voltage waves. These four waves are related by the following equations where s11, s12, s21 and s22 are the ‘scattering’, or s-para- b1 = s11a1 + s12a2 (3.15) b2 = s21a1 + s12a2 (3.16) Equations 3.15 and 3.16 are also written in matrix form as ⎡ b1 ⎤ ⎡ s11 s12 ⎤ ⎡ a1 ⎤ ⎢b ⎥ = ⎢ s ⎥⎢ ⎥ (3.17) ⎣ 2 ⎦ ⎣ 21 s22 ⎦ ⎣a2 ⎦ When scattering parameters are to be measured, the applied source is a generator which has the source impedance Z 0 equal to the system characteristic impedance and this generator is connected to the system by a line of characteristic impedance Z 0, as in Figure 3.27. The load is purely resistive, with impedance Z 0, and connected by a line of impedance Z 0. So the source seen by the two port’s input is Z 0, and the load seen by its output is also Z 0. In this case, there is no power reflected from the load, so a 2 = From Equation 3.15, if a 2 = 0, then b1 = s11a1. So s11 can be defined as Scattering parameters (s-parameters) 127 Fig. 3.27 Measurement of s-parameters s11 = (3.18) a1 a2 = 0 and s11 is the reflection coefficient at the input port (port 1) of the network. From Equation 3.16, with a2 = 0, b2 = s21a1. So s21 can be defined as s21 = (3.19) a1 a2 = 0 Since this is the ratio of the output wave voltage to the incident wave voltage, |s21|2 is the insertion power gain of the network. The other two s-parameters, s12 and s22, are found by inter-changing the electrical connections to the two ports, so that port 2 is driven from the source, and port 1 is loaded by Z 0. Now a1 = 0, and s12 = (3.20) a2 a1 = 0 s22 = (3.21) a2 a1 = 0 |s12| 2 is the reverse insertion power gain, and s22 is the output port reflection coefficient. It should be clear, but two points are worth stressing. • The scattering parameters are defined, and measured, relative to a fixed system imped- ance Z 0. In practice, the chosen value is nearly always 50 Ω resistive. • The scattering parameters are complex quantities, representing ratios of phasors at a defined plane at each port. It is now necessary to define symbols a1, a 2, b1 and b2 in terms of voltages and currents. 3.10.3 Incident and reflected waves in scattering parameters It will ease understanding if the explanation of incident and reflected waves is taken in two parts. We will begin with the ‘ideal’ situation where there is complete match within the 128 Smith charts and scattering parameters Fig. 3.28 ‘Ideal’ two-port network system, i.e. where the source generator, connecting lines, two-port network and load impedance all have characteristic impedances of Z 0. Then, we will proceed with the real life practical situation where the two-port network does not match the measuring system. In Figure 3.28, we consider the ideal situation where a generator (vs ) with an internal impedance Z 0 feeds a transmission line whose impedance is Z 0 which in turn feeds a two- port network whose input and output impedances are Z 0. The output from the two-port network is then fed through another transmission line of Z 0 to a termination load where Z L = Z 0. In other words because everything in the system matches, we have no reflected power, therefore the incident voltage (vi ) represents the input voltage to the network and the incident current (i i ) represents the current flowing into the network. Now consider the practical case (Figure 3.29) where the-two port network is not matched to the same system. Due to the mismatch, we will now have reflected power. This reflected power will produce a reflected voltage vr and a reflected current i r. If we now defined v1 as being the sum of the incident and reflected voltages and i1 as the difference of the incident and reflected currents, we have v 1 = v i + vr (3.22) i1 = ii – ir (3.23) By the definition of impedances, we have vi vr Z0 = — = — (3.24) ii ir Fig. 3.29 Practical two-port network Scattering parameters (s-parameters) 129 Equation 3.24 can be re-written to yield ii = (3.25) ir = (3.25a) Substituting Equations 3.25 and 3.25a into Equation 3.23 gives vi v il = − r Z0 Z0 Z 0 i1 = v i – v r (3.26) Adding Equations 3.22 and 3.26 yields 2v i = v1 + Z 0 i1 v i = — [v1 + Z 0 i1] (3.27) Subtracting Equation 3.26 from Equation 3.22 yields 2v r = v1 – Z 0i1 v r = — [v1 – Z 0 i 1] (3.28) The incident wave v i is defined as the square root of the incident power. Therefore, vi2 v a1 = = i (3.29) Z0 Z0 Using Equation 3.27 to substitute for v i in Equation 3.29 and dividing by Z0 , we get vi 1⎡ v ⎤ a1 = = ⎢ l + Z0 i1 ⎥ (3.30) Z0 2 ⎢ Z0 ⎣ ⎥ Similarly, the reflected wave v r is defined as the square root of the reflected power. vr v b1 = = r (3.31) Z0 Z0 130 Smith charts and scattering parameters Using Equation 3.28 to substitute for v r in Equation 3.31 and dividing by Z0 , we vr 1⎡ v ⎤ b1 = = ⎢ 1 − Z0 i1 ⎥ (3.32) Z0 2 ⎢ Z0 ⎣ ⎥ Again using similar arguments, it can be shown that 1 ⎡ v2 ⎤ a2 = ⎢ + Z0 i2 ⎥ (3.33) 2 ⎢ Z0 ⎣ ⎥ 1 ⎡ v2 ⎤ b2 = ⎢ − Z0 i2 ⎥ (3.34) 2 ⎣ Z0 ⎥ Thus, we have now evaluated a1, a 2, b1 and b 2 in terms of incident voltages and currents and the characteristic impedance of the measuring system. 3.10.4 S-parameters in terms of impedances From Equations 3.18, 3.27, 3.28, 3.30 and 3.32 we write 1 i1 ⎡ v1 ⎤ [v1 − Z0 i1 ] 2 ⎢ i − Z0 ⎥ = ⎣1 ⎦ s11 = 1 = 2 a1 a = 0 1 [v + Z i ] i1 ⎡ v1 ⎤ 1 01 ⎢ + Z0 ⎥ 2 ⎣ i1 ⎦ and since v1/i1 = input impedance at port 1 of the two-port network which we will call Z1, we have b1 Z1 − Z0 s11 = = (3.35) a1 a2 = 0 Z1 + Z0 Note that Z 1 is really the load for the signal generator in this case; in some cases, it is common to write Z L instead of Z 1 which makes Equation 3.35 identical to the transmis- sion line reflection coefficient (Γ1) so that we have b1 Z L − Z0 s11 = = = Γ1 (3.36) a1 a2 = 0 Z L + Z0 Equation 3.36 also confirms what we have shown in Figure 3.3 that when the input impedance of the two-port network = Z 0, the reflection coefficient is zero and that there is no reflected wave. Using the same process as above, it is possible to show that Applied examples of s-parameters in two port networks 131 b2 Z2 − Z0 s22 = = = Γ2 (3.37) a2 a1 = 0 Z2 + Z0 where Z 2 is the driving impedance of output port (port 2) of the two-port network. 3.10.5 Conversion between s-parameters and y-parameters Most radio frequency measurements are now carried out using automated computer controlled network analysers with error correction. The measurements are then converted from s-parameters to other types of parameters such as transmission parameters (ABCD), hybrid h-parameters, and admittance y-parameters. We provide you with Table 3.6 to enable conversion between s- and y-parameters. Table 3.6 Conversion between scattering s-parameters and y-parameters (1 − y11 )(1 − y22 ) + y12 y21 ⎛ (1 + s22 )(1 − s11 ) + s12 s21 ⎞ 1 s11 = † y11 = ⎜ ⎟ * (1 + y11 )(1 + y22 ) − y12 y21 ⎝ (1 + s11 )(1 + s22 ) − s12 s21 ⎠ Z0 −2 y12 ⎛ −2 s12 ⎞ 1 s12 = † y12 = ⎜ * (1 + y11 )(1 + y22 ) − y12 y21 ⎟ ⎝ (1 + s11 )(1 + s22 ) − s12 s21 ⎠ Z0 −2 y21 ⎛ −2 s21 ⎞ 1 s21 = † y21 = ⎜ ⎟ * (1 + y11 )(1 + y22 ) − y12 y21 ⎝ (1 + s11 )(1 + s22 ) − s12 s21 ⎠ Z0 (1 + y11 )(1 − y22 ) + y12 y21 ⎛ (1 + s11 )(1 − s22 ) + s12 s21 ⎞ 1 s22 = † y22 = ⎜ ⎟ * (1 + y11 )(1 + y22 ) − y12 y21 ⎝ (1 + s11 )(1 + s22 ) − s12 s21 ⎠ Z0 * where Z 0 = the characteristic impedance of the transmission lines used in the scattering parameter system, usually 50 W. † Notice that when you are converting from admittance (Y) to s-parameters, (left hand column of Table 3.6), each individual Y parameter must first be multiplied by Z 0 before being substituted into the equations. 3.11 Applied examples of s-parameters in two-port networks Most people who have not encountered s-parameters earlier tend to find s-parameter topics a bit abstract because they have only been used to tangible voltages, currents and lumped circuitry. In order to encourage familiarity with this topic, we offer some examples. 3.11.1 Use of s-parameters for series elements Example 3.15 Calculate the s-parameters for the two-port network shown in Figure 3.30 for the case where Z 0 = 50 Ω. Given: Network of Figure 3.30 with Z 0 = Z L = 50 Ω. Required: s-parameters. 132 Smith charts and scattering parameters Fig. 3.30 Resistive network s11: Terminate the output in Z 0 and determine Γ1 at the input. See Figure 3.31(a). By inspection: Z 1 = 50 W + 50 Ω = 100 Ω From Equation 3.36 Z1 − Z0 100 − 50 1 s11 = Γ1 = = = Z1 + Z0 100 + 50 3 s11 = 0.333 ∠ 0° or –9.551 dB ∠ 0° s22: Terminate the input with Z 0 and determine Γ2 at the output. See Figure 3.31(b). By inspection: Z 2 = 50 Ω + 50 Ω = 100 Ω From Equation 3.37 Z2 − Z0 100 − 50 1 s22 = Γ2 = = = Z2 + Z0 100 + 50 3 s22 = 0.333 ∠ 0° or –9.551 dB ∠ 0° Note: s11 and s 22 are identical. This is what you would expect because the network is Fig. 3.31(a) Calculating s 11 Fig. 3.31(b) Calculating s 22 Applied examples of s-parameters in two port networks 133 2v1+ v2 v1 2v2+ Fig. 3.31(c) Calculating s 21 Fig. 3.31(d) Calculating s 12 s21: Drive port 1 with the 50 Ω generator and open-circuit voltage of 2V1+. The multi- plication factor of 2 is used for mathematical convenience as it ensures that the voltage incident on the matched load will be V1+. The superscript + sign following the voltage is meant to indicate that the voltage is incident on a particular port. Calculate voltage V2. See Figure 3.31(c). V0 V2 s21 = = V1+ V1+ By inspection: V2 + = (2V1+ ) = (2V1+ ) = V1+ 50 + (50 + 50) 150 3 V0 V2 2V + 2 s21 = = = 1+ = V1+ V1+ 3V1 3 s 21 = 0.667 ∠ 0° or –3.517 dB ∠ 0° s12: See Figure 3.31(d). By inspection: V1 = (2V2+ ) = V2+ 50 + (50 + 50) 3 V1 2V + 2 s12 = = 2 = V2+ 3V2+ 3 s12 = 0.667∠0° or − 3.517 dB ∠0° Note: s12 and s 21 are the same because the network is symmetrical. Summing up For s-parameters: s11 = 0.333 ∠ 0° s 12 = 0.667 ∠ 0° s 21 = 0.667 ∠ 0° s 22 = 0.333 ∠ 0° 134 Smith charts and scattering parameters or in matrix notation [s] = [ 0.333 ∠ 0° 0.667 ∠ 0° 0.667 ∠ 0° 0.333 ∠ 0° ] Later on, you will see that this symmetry in a network often leads to considerable simpli- fication in manipulating networks. 3.11.2 Use of s-parameters for shunt elements Example 3.16 Calculate the s-parameters for the two port network shown in Figure 3.32 for the case where Z 0 = 50 Ω. Given: Network of Figure 3.32 with Z 0 = Z L = 50 Ω. Required: s-parameters. Fig. 3.32 Resistive network s11: Terminate the output in Z 0 and determine Γ1 at the input. See Figure 3.33(a). By (50 × 50)Ω Z1 = = 25 Ω (50 + 50)Ω From Equation 3.36 Z1 − Z0 25 − 50 −1 S11 = Γ1 = = = Z1 + Z0 25 + 50 3 s11 = 0.333 ∠ 180° or –9.551 dB ∠ 180° s22: Terminate the input with Z 0 and determine Γ2 at the output. See Figure 3.33(b). By (50 × 50) Ω Z 2 = ————— = 25 Ω (50 + 50) Ω Applied examples of s-parameters in two port networks 135 Fig. 3.33(a) Calculating s11 Fig. 3.33 (b) Calculating s 22 From Equation 3.37 Z1 – Z 0 25 – 50 –1 s22 = r 2 = ———— = ———— = —— Z1 + Z 0 25 + 50 3 s22 = 0.333 ∠ 180° or –9.551 dB ∠ 180° Note: s11 and s 22 are identical. This is what you would expect because the network is s21: Drive port 1 with the 50 Ω generator and open-circuit voltage of 2V1+. The multi- plication factor of 2 is used for mathematical convenience as it ensures that the voltage incident on the matched load will be V1+. The superscript + sign following the voltage is meant to indicate that the voltage is incident on a particular port. Calculate voltage V2. See Figure 3.33(c). V0 V2 s21 = —— = —— V1+ V1+ By inspection and bearing in mind that two 50 W resistors in parallel = 25 Ω V2 = (2V1+ ) = (2V1+ ) = V1+ 50 + 25 75 3 2V1+ 2 s21 = = 3V1+ 3 s 21 = 0.667 ∠ 0° or –3.517 dB ∠ 0° s12: See Figure 3.33(d). By inspection, and bearing in mind that two 50 Ω resistors in parallel = 25 Ω V1 = (2V2+ ) = V2+ 50 + 25 3 136 Smith charts and scattering parameters 2v1+ v2 v1 2v2+ Fig. 3.33(c) Calculating s 21 Fig. 3.33(d) Calculating s12 V1 2V + 2 s12 = = 2 = V2+ 3V2+ 3 s 12 = 0.667∠ 0° or –3.517 dB ∠ 0° Note: s12 and s22 are the same because the network is symmetrical. Summing up For s-parameters: s11 = 0.333 ∠ 180° s12 = 0.667 ∠ 0° s 21 = 0.667 ∠ 0° s 22 = 0.333 ∠ 180° 3.11.3 Use of s-parameters for series and shunt elements Example 3.17 (a) Calculate the s-parameters for the two-port network shown in Figure 3.34 for the case where Z 0 = 50 Ω. (b) Find the return loss at the input with Z L = Z 0. (c) Determine the insertion loss for the network when the generator and the termination are both 50 Ω. Given: Network of Figure 3.34 with Z 0 = Z L. Required: (a) s-parameters, (b) return loss, (c) insertion loss. Fig. 3.34 Complex network Applied examples of s-parameters in two port networks 137 (a) s11: Terminate the output in Z 0 and determine ρ at the input. See Figure 3.35(a). By inspection the combined value of the 30 Ω and 50 Ω resistors is: (30 × 50)/(30 + 50) = 18.75 Ω Z 1 = 18.75 Ω + j20 Ω From Equation 3.36 Z1 − Z0 (18.75 + j20) − 50 s11 = ρ1 = = Z1 + Z0 (18.75 + j20) + 50 −31.25 + j20 37.10∠147.38° = = 68.75 + j20 71.60∠16.22° s11 = 0.518 ∠ 131.16° or –5.713 dB ∠ 131.16° s22: Terminate the input with Z 0 and determine ρ at the output. See Figure 3.35(b). By (50 + j20)(30) 1500 + j600 Z2 = = (50 + j20 + 30) 80 + j20 = = 19.591 ∠ 7.765° or 19.412 + j2.647 From Equation 3.37 Z2 − Z0 (19.412 + j2.647) − 50 −30.588 + j2.647 s22 = ρ2 = = = Z2 + Z0 (19.412 + j2.647) + 50 69.412 + j2.647 30.702 ∠ 175.054° = = 0.442 ∠ 172.870° 69.462 ∠ 2.184° s22 = 0.442 ∠ 172.87° or –7.092 dB ∠ 172.87° Fig. 3.35(a) Calculating s11 Fig. 3.35(b) Calculating s22 138 Smith charts and scattering parameters 2v1+ v2 Fig. 3.35(c) Calculating s21 s21: Drive port 1 with the 50 Ω generator and open-circuit voltage of 2V1+. The multi- plication factor of 2 is used for mathematical convenience as it ensures that the voltage incident on the matched load will be V1+. The superscript + sign following the voltage is meant to indicate that the voltage is incident on a particular port. Measure voltage across V2. See Figure 3.35(c). V0 V2 s21 = = V1+ V1+ By inspection: 30 // 50 18.75 V2 = (2V1+ ) = (2V1+ ) 30 // 50 + (50 + j20) 68.75 + j20 (18.75)(2V1+ ) = = (0.524 ∠ − 16.22°)V1+ 71.60 ∠ 16.22° (0.524 ∠ –16.22°)V1+ s21 = ————————— s21 = 0.524 ∠ –16.22° or – 5.613 dB ∠ –16.22° s12: The Thévenin equivalent of the generator to the right of the plane ‘c c’ is obtained first. See Figures 3.35(d) and 3.35(e). v2 2v2+ Fig. 3.35(d) Circuit before applying Thévenin’s theorem Applied examples of s-parameters in two port networks 139 v2 0.75v2+ Fig. 3.35(e) Circuit after applying Thévenin’s theorem The Thévenin equivalent generator voltage is (2V2+ ) = 0.75V2+ 30 + 50 The Thévenin equivalent internal resistance is 30 × 50 = 18.75 Ω 30 + 50 By inspection: 50 37.5 V1 = (0.75V2+ ) = V2+ (18.75 + 50 + j20) 71.60 ∠ 16.22° = 0.524 ∠ − 16.22° V1 (0.524 ∠ − 16.22°)V2+ s12 = = = 0.524 ∠ − 16.22° V2+ V2+ s12 = 0.524 ∠ –16.22° or –5.613 dB ∠ –16.22° To sum up for s-parameters (a) s11 = 0.518 ∠ 131.16° s12 = 0.524 ∠ –16.22° s21 = 0.524 ∠ –16.22° s22 = 0.442 ∠ 172.87° (b) From part (a), Γ ∠ θ = 0.518 ∠ 131.16°. Therefore return loss (dB) = –20 log10 |0.518| = –20 × (–0.286) = 5.713 dB (c) The forward power gain of the network will be |s21| 2. |s21| 2 = (0.524)2 = 0.275 This represents a loss of –10 log10 0.275 = 5.61 dB. 140 Smith charts and scattering parameters 3.11.4 Use of s-parameters for active elements Example 3.18 A 50 Ω microwave integrated circuit (MIC) amplifier has the following s-parameters: s11 = 0.12 ∠ –10° s12 = 0.002 ∠ –78° s21 = 9.8 ∠ 160° s22 = 0.01 ∠ –15° Calculate: (a) input VSWR, (b) return loss, (c) forward insertion power gain and (d) reverse insertion power loss. Given: s11 = 0.12 ∠ –10° s12 = 0.002 ∠ –78° s21 = 9.8 ∠ 160° s22 = 0.01 ∠ –15° Required: (a) Input VSWR, (b) return loss, (c) forward insertion power gain, (d) reverse insertion power loss. (a) From Equation 2.38 1 + Γ 1 + s11 1 + 0.12 VSWR = = = 1 − Γ 1 − s11 1 − 0.12 = 1.27 (b) Return loss (dB) = –20 log10 0.12 = 18.42 dB (c) Forward insertion gain = |s21| 2 = (9.8)2 = 96.04 or Forward insertion gain = 10 log10 (9.8)2 dB = 19.83 dB (d) Reverse insertion gain = |s12| 2 = (0.002)2 = 4 × 10–6 or Reverse insertion gain = 10 log10 (0.002)2 dB = –53.98 dB The amplifier is virtually unilateral with (53.98 – 19.83) or 34.15 dB of output to input 3.12 Summary of scattering parameters Section 3.10 has been devoted to the understanding of two-port scattering networks. Section 3.11 has been devoted to the use of two-port scattering networks. You should now be able to manipulate two-port networks skilfully and have the ability to change two-port parameters given in one parameter set to another parameter set. An excellent understanding of scattering parameters is vitally important in microwave engineering because most data given by manufacturers are in terms of these parameters. In fact, you will find it difficult to proceed without a knowledge of s-parameters. This is the reason why we have provided you with several examples of s-parameter applications. The examples will be repeated using a software program called PUFF which has been supplied to you with this book. The purpose of these software exercises is to reinforce the concepts you have learnt and also to convince you that what we have been doing is correct. Do not be unduly perturbed if you initially found s-parameters difficult to understand. Summary of scattering parameters 141 Understanding of s-parameters is slightly more difficult because they deal with waves, which is a very different concept from the steady-state voltages and currents which we have used in the past. Finally, the information you have acquired is very important because most information in radio and microwave engineering is given in terms of scattering and admittance para- meters. We have devoted particular attention to s-parameters because, later on, when you start analysing microwave components, filters, amplifiers, oscillators and measurements, you will be confronted with scattering parameters again and again. This is the reason why we have provided you with many examples on the use of scattering parameters. PUFF software 4.1 Introduction 4.1.1 Aims The aims of this chapter are threefold: (i) to help you install software program PUFF 2.1 on your computer; (ii) to use PUFF (software program supplied with this book) to verify the examples which you had worked with in the earlier chapters; and (iii) to give you confi- dence in using the software. The software program that we introduce here is known as PUFF Version 2.1 It is a radio and microwave design and layout computer program developed by the California Institute of Technology (CalTech) Pasadena, USA. The program has been licensed to the publishers for use with this book. The conditions of the licence are that you use it for private study and experimental designs, and that copies of the program must not be made available to the general public and on the Internet, World Wide Web, etc. For ease of understanding, in all the discussions that follow, we will refer to PUFF Version 2.1 as Note: When installed on a computer with a colour monitor, PUFF displays a default colour screen. In the descriptions that follow, it is not feasible to display colour pictures, and every effort has been made to annotate the graphs. However, if you still have difficulty, run PUFF on your computer using the PUFF examples supplied on the PUFF disk. In fact, set up each example and check the results for yourself. It will give you confidence in using To install your software and to be able to manipulate the program, read Sections 4.2 to 4.10. 4.1.2 Objectives The objectives of Part 4 are to teach you how to use PUFF for the following topics: • amplifier designs • calculating s-parameters for circuits • calculating s-parameters for distributed components • calculating s-parameters for lumped components • circuit layout Installation of PUFF 143 • coupled circuits • filter frequency response and matching • line transformer matching and frequency response • stub line matching and frequency response • transistor matching and frequency response 4.2 CalTech’s PUFF Version 2.1 CalTech’s PUFF is a computer program that allows you to design a circuit using pre- selected lumped components (R, L, C and transistors) and/or distributed components (microstrip lines and striplines variants). The components may be arranged to form circuits. The layout of the circuit can be computer magnified, printed to provide a template for printed circuit layout and construction. The program provides facilities for calculating the scattering parameters (s-parameters) of the designed circuit layout with respect to frequency. The results can be read directly, plotted in Cartesian coordinates (X-Y plots) and in Smith chart impedance or admittance form. The Smith chart can also be used for match- ing purposes and for oscillator design. 4.3 Installation of PUFF 4.3.1 Introduction The following notes are written with the express objective of explaining how to install PUFF on a personal computer. CalTech’s PUFF is supplied on a compact disk. The program is designed to work on all PC, IBM PC/XT/AT and compatible computers. The minimum hardware requirements for the computer are a CD drive, a hard disk, 640K RAM and a 80286 or higher processor. If you do not have a CD drive, then ask a friend to copy all the PUFF folder files to a high density 3.5″ disk for transfer to your hard disk. The processor should have its matching coprocessor; if no coprocessor is present PUFF will run in its floating point mode and operate less rapidly. MS-DOS(R) versions 3.0 or higher should be used. All printed outputs are directed to the parallel port LPT1. Printing graphic screens requires an Epson or a Laser compatible printer. PUFF provides six printer drivers for ‘screen dumps’. 4.3.2 Installation In the instructions which follow, I will use these conventions. • Bold letters for what you have to type. • Plus signs to indicate that two or more keys must be pressed together. For example, ctrl + f means that you keep the ctrl key pressed down while you type f. Similarly alt + shift + g means that you keep the alt and shift keys pressed down while you type g. • The output from the screen is shown in italics. • To simplify explanation I shall assume that your hard disk is c: and that you are installing from drive a:. If your hard disk drive is not c: then substitute the drive letter of your hard 144 PUFF software disk drive whenever you see c:. If you are not installing from drive a:, then substitute the drive letter of your drive whenever you see a:. 4.3.3 Installing PUFF This program is relatively small. It is not compressed. It can be run directly from the supplied disk initially. We do not recommend that you do this because if you damage your original disk, then you will not have a ‘back-up’ program. We recommend that you run PUFF from a directory on your hard disk. You install it simply by making a directory called PUFF on your hard disk and copy all programs including the sub-directory VGA_eps from your diskette to your PUFF directory. Details are given in the following Windows installation 1 Insert your PUFF disk in drive a:. 2 Start Windows in the usual manner and ensure that the Program Manager is 3 From Program Manager, click on the main menu and select File Manager. 4 From the File menu, select create a directory. In the Create Directory box type c:puff. Press the RETURN key. 5 Keep in the File Manager window. Click on disk a on the menu bars to display all the files on disk a:. 6 Select all items on disk a: and copy them all to the new directory PUFF which you have just created. You select copy from the File menu in File Manager. Press the RETURN key. When presented with the Copy box, type c:puff. Press the RETURN key. 7 All PUFF folder files from disk a: should be copied in your directory c:PUFF. 8 Installation is now complete. DOS installation 1 Insert the PUFF disk in drive a:. 2 Create a directory PUFF using the DOS MKDIR command. At the DOS prompt C:\>, type MKDIR PUFF and press the RETURN key. 3 To copy all the files from the PUFF disk in drive a: into the directory C :\PUFF. type COPY A: *.* C:\PUFF\*.* and press the RETURN key. 4 Check that all the files including subdirectory VGA_eps have been copied into your PUFF directory by typing DIR C:\PUFF\*.* and press the RETURN key. 4.4 Running PUFF 4.4.1 Running under Windows PUFF will run in a DOS window if accessed via File Manager in Windows 3.1 or My Computer or Windows Explorer or File Manager in Windows 95, 98 and ME. The ability of Windows to support PUFF is dependent on computer memory. If you attempt unsuc- cessfully the techniques below, then close down Windows and follow the DOS instructions. Running PUFF 145 Running under Windows 3.1 Double click on the c:PUFF directory in File Manager. Double click on PUFF.exe. PUFF should load into a DOS window. An alternative to this is to double click on the MSDOS icon and follow the DOS instructions in Section 4.4.2. Running under Windows 95/98/2000 My Computer 1 Double click on the My Computer icon on the Windows Desktop. 2 Double click on [c:]. 3 Double click on the PUFF folder icon. 4 Double click on the PUFF program icon. PUFF should now run in a DOS window. Windows Explorer 1 Select Programs from the Start menu. 2 Click on Windows Explorer. 3 Double click on the c:PUFF folder. 4 Double click on the PUFF application. PUFF should load into a DOS window. An alternative to either of these methods is to select Programs from the Start menu, then choose the MS-DOS prompt and follow the DOS instructions. 4.4.2 DOS instructions To run PUFF, you must first call up the directory PUFF and then type PUFF to start the program. Follow this procedure. 1 Type CD C:\PUFF and press the RETURN key. On the screen you should see 2 Type PUFF and press the RETURN key. The program will start with an information text screen giving details of the program and your computer. This is essentially an information sheet. At the last line, it will say Press ESC to leave the program or any other key to continue. Type any key. If your computer has a colour monitor then you will see Figure 4.1 in colour. Otherwise you will see it in monochrome. Throughout this block, I will use monochrome but where or when necessary, I will add annotation to enable easy identification of program parame- ters. The Figure 4.1 screen has been set by a template called setup.puf which is called up automatically when you start the program without defining a particular template. Templates are used to keep the program size small so that PUFF remains versatile and will run on personal computers. This template specifies the physical properties (size, thickness, dielectric constant, terminal connections) and the electrical parameters (dielectric constant, dielectric loss tangent, metal conductivity, etc.) of the board which will be used to construct the circuit. Frequency ranges and components are also defined by the template. Some of these properties can be changed directly within the program, others will have to be changed by modifying the template. We will show you how to change these properties later, but for now just accept the default template. 146 PUFF software Fig. 4.1 Default screen for PUFF (words in italics have been added for easy identification) We will now examine the elements of Figure 4.1. 1 Box F1: LAYOUT is a blank board on which we design our circuit. We can insert and join up many types of components on it. 2 Box F2: PLOT specifies the parameters which will be used for plotting the circuit. You can change these parameters and plot up to four s-parameters simultaneously. Within limits, you can also change the frequency and the number of plotting points. 3 Message Box between F2 and F3. This box is an information box used for communi- cations between the user and the program. It is normally blank when the program is started. It can also be used to yield S11, S22, S33, S44 in terms of impedance or admit- 4 Box F3: PARTS specifies the components which can be used in the design. At the moment, we have only shown seven components but you can specify up to 18 different components in the design. These can be resistors, capacitors, inductors, transistors, transformers, attenuators, lossless transmission lines (tlines), lossy transmission lines (qlines) and coupled lines (clines). If on your screen, you see Ü instead of Ω, then your machine has been configured differently to the way expected by the program. This will not affect your work but just make a note that Ü means Ω. 5 Box F4: BOARD displays some of the layout board properties. It tells you that the impedance (zd) of the connecting lines, its source impedance and load impedance are 50 W. It specifies the dielectric constant (er) of the board as 10.2 at 5 GHz. The Examples 147 thickness (h) of the board is 1.27 mm, its size (s) is 25.4 mm square and the distance between connectors (c) is 19.00 mm. The board is configured for microstrip layout. 6 The Smith chart on the top right side shows you the s-parameters of the designed circuit. It can also be expanded and changed into admittance form. 7 The Rectangular plot (amplitude vs frequency graph) at the bottom of the screen plots s-parameters in dB against frequency. In future, I will simply call this plot the rectan- gular plot. 8 Pressing the F10 key will give you a small help screen. 4.5 Examples The use of the above properties will now be illustrated. 4.5.1 Example 4.1 Example 4.1 is relatively simple but it does help you gain confidence in using the program. We will start by constructing a 50 W transmission line on the layout board. This is shown in Figure 4.2. To carry out the above construction proceed as follows. 1 If necessary switch your computer on, call your PUFF directory, type PUFF, press the RETURN key and you should get Figure 4.1. Fig. 4.2 Diagram showing a 50 W transmission line 148 PUFF software 2 Press the F4 key. F4 will now be highlighted and you will be permitted to change values in the F4 box. An underlined cursor will appear on the zd line. Press the down arrow key (five times) until you get to the c 19.00 mm line. Throughout this set of instructions, keep looking at Figure 4.2 for guidance and confirmation of your actions. 3 Press the right arrow key until the cursor is under the 1 on the line, then type 00 (zero). Line c should now read c 00.000 mm. What you have effectively done is reduce the spacing between connectors 1 and 3, and 2 and 4 to zero. You will not see the effect as yet. 4 Press the F1 key. F1 will now be highlighted and you will be permitted to lay compo- nents in the F1 box. An X will appear in the centre of the board. Note that there are now only two connecting terminals on the centre edges of the board. This is because of the action carried out in step 3. Notice also that in the F3 box, line a is highlighted. This means that you have selected a lumped 150 W resistor to be put on the board. We do not want this; we only want the 50 W transmission line on line b to be selected, so type b. Line b tline 50 W 90° will be highlighted. 5 Press the left arrow key and you will see the circuit of Figure 4.2 emerging. (If you make any mistake in carrying out these instructions, erase by retracing your step with the shift key pressed down. For example, if you want to erase what you have just done, press shift+right arrow keys. You can also erase the entire circuit by pressing ctrl+e 6 Type 1 and the tline will be joined to terminal 1. 7 Press right arrow key twice. See Figure 4.2. 8 Type 2 to join the right-hand section of line to terminal 2. Our circuit is now complete and we have put two sections of 50 transmission line (b) between a 50 W generator and load. We are now in a position to investigate its electrical properties. 9 Press the F2 key. F2 will now be highlighted and you will be permitted to specify your measurement parameters in the F1 box. 10 Press the down arrow key three times. This will produce a new line XS. 11 Type 21 because we want to measure the parameters S11 and S21. Again refer to Figure 4.2 for guidance. 12 Type p to plot your parameters. You will now get Figure 4.2. 13 If you do not get this figure then repeat the above steps. 14 To save Figure 4.2, press the F2 key. Type Ctrl+s. In the message box you will see File to save? Type TX50 and press the RETURN key. Figure 4.2 is now saved under the file name TX50. I will now explain to you the meaning of Figure 4.2. From the F2 box, you can see that we have measured S11 and S21 over 21 frequency points within the frequency range from 0–10 GHz. This frequency range is marked on the rectangular plot (amplitude vs frequency graph) on the bottom right-hand side of the screen. S21 is indicated on the graph and on the outer periphery of the Smith chart. (If you have a colour monitor, it is the blue line.) S11 is indicated on the centre of the Smith chart. S11 cannot be shown on the rectan- gular plot because its value is minus infinity and outside the range of the plot. PUFF reports any magnitude as small as –100 dB as zero and any magnitude greater than 100 dB as zero. You can also obtain the values of S11 and S21 at discrete frequency points by referring to the F2 box. At the moment, it is showing that at 5 GHz, S11 = 0 and S21 = 0 dB (ratio Examples 149 of 1). This is expected because the reflection coefficient (S11) is zero and as tlines are considered as lossless lines in the program, the gain (S21) is also zero. You can also check the input impedance of the line by moving the cursor to the S11 line and typing = . The actual value of the input line is shown on the Message box as Rs = 50 and Xs = 0. This tells you that the input impedance of the line is 50 W. You should still be in the F2 mode. Press the PageUp key and watch the changes of frequency, S11, and S21 in the F2 box. In addition the symbols for S11 and X for S21 also move on the Smith chart and the rectangular plot. Press this again and watch the same movement. To lower the frequency, press the PageDown key and watch the same parame- ters noted previously. Note the PageUp and PageDown keys will only function when F2 is highlighted. The reason why you do not see drastic changes in the S-parameters is because from theory, we know that a lossless transmission with a characteristic impedance of 50 W inserted within a matched 50 system will only produce phase changes with 4.5.2 Smith chart expansion While we are in F2 mode, it is also possible to expand the Smith chart to get a clearer view. Press alt+s. You will now get Figure 4.3. You can also press the TAB key to change the Smith chart form into an admittance display. See Figure 4.4. When you have finished, use alt+s to toggle back to the normal display. Remember the Fig. 4.3 An expanded view of the Smith chart in impedance mode 150 PUFF software Fig. 4.4 An expanded view of the Smith chart in admittance mode TAB and alt+s actions act as toggle switches and only perform these functions when the F2 box is active. Another point that you should be aware of is that in the F2 mode, if you press the TAB key to change the Smith chart from impedance to admittance and if you move the cursor to S11 and type = , you will get the parallel values of the line rather than the series values mentioned earlier. 4.5.3 Printing and fabrication of artwork If you have the proper printer connected, you should be able to print out the layout for photo-etching purposes to make the actual printed circuit board. The print-out shown in Figure 4.5 is five times the actual physical size of the layout. The magnification of the layout is chosen to reduced the ‘jagged edges’ (constant in a printer) to an insignificant width of the line. The print-out is then photographed, and reduced back to the original layout size. In the photographic reduction process, these jagged edges are also reduced by five, so that its effect on the true width of the line is less. The net result is that the line impedance is reproduced more accurately. Note: Do not attempt to print at this time; it will be covered later. Examples 151 Fig. 4.5 Print-out of microstrip line 4.5.4 Summary of Example 4.1 From Example 4.1 you have learnt how to use PUFF to: 1 change the position of the terminal connections (c in F4 mode); 2 select parts from the Parts Board (b in F3 mode); 3 layout and connect selected components to the board terminals; erase your layout circuit or components (ctrl+e, shift+arrow, in F1 mode); 4 plot and read the results of your circuit layout (S11 and S21 in F2 mode); 5 expand the Z- and Y-display of the Smith chart for more accurate readings (alt+s and TAB in F2 mode); 6 be able to obtain series and parallel values using S11 and the = sign; 152 PUFF software 7 save a file; 8 print out your layout for subsequent circuit construction. Now try Example 4.1 on your own to see if you have remembered the procedures. 4.6 Bandpass filter The electrical results of Example 4.1 have not been too interesting because it is commonly known that if a lossless 50 W line is inserted into a 50 W system, then little change, other than phase, takes place. However, it was deliberately chosen to produce minimum confu- sion in learning how to use the program and also to show that the program actually produces a well known and expected result. 4.6.1 Example 4.2 In Example 4.2, we will become a bit more adventurous and introduce some quarter-wave line short-circuited stubs across the junctions A, B, and C in the system. This case is shown in Figure 4.6. The procedure for Example 4.2 is almost identical to that for Example 4.1 except that you will have to remember (i) that to short-circuit a component to the ground plane, you must type the equal (=) sign at the end you want grounded; and (ii) to lay a component in the vertical direction, you must type either the up arrow key or the down arrow key. Fig. 4.6 Bandpass filter using quarter-wave lengths of line Bandpass filter 153 In Figure 4.6, we have produced a bandpass filter centred at the centre frequency ƒ0 (5 GHz in this case) where the lines are exactly a quarter-wave long. You will no doubt remember from previous transmission line theory that the transformation of a l/4 line is Z in = Z 02 /Z load. At ƒ0, all three short-circuited lines produce an infinite impedance across junctions A, B, and C. This means that signal transmission is unimpaired at ƒ0, and you will get an identical result to that of Example 4.1, i.e. the 180° phase shift and, since tlines in this program are assumed to be lossless, you will also obtain zero When the frequency is not ƒ0, then the shorted stubs do not present infinite impedances1 at the junctions. At ƒ < ƒ0, the shorted stubs will be inductive and will shunt signal to ground. At ƒ > ƒ0, the shorted stubs will be capacitive and shunt signal to ground. The result is shown in Figure 4.6. I suggest that you try to reproduce Figure 4.6 on your own but do not despair if you do not succeed because the details are given below. However, here are a few hints which might prove useful before you begin. Hint: From F1 use the down arrow keys when you want to lay a component downwards, an up arrow key when you want to move upwards and use the equal sign (=) key when you want to ground a component. Now carry out the relevant procedures of Example 4.2. If you are still unable to get Figure 4.6, then carry out the instructions given below but throughout this set of instructions, keep looking at Figure 4.6 for guidance and confirma- tion of your actions. 1 If necessary switch on your computer. Call your PUFF directory, type PUFF, press the RETURN key and you should get Figure 4.1. 2 Press the F4 key. F4 will now be highlighted and you will be permitted to change values in the F4 box. An underlined cursor will appear on the zd line. Press the down arrow key (five times) until you get to the c 19.00 mm line. 3 Press the right arrow key until the cursor is under the 1 on the line, type 00 (zero). Line c should now read c 00.000 mm as in Figure 4.6. What you have effectively done is reduce the space between connectors 1 and 3, and 2 and 4 to zero. You will not see the effect as yet. 4 Press the F1 key. F1 will now be highlighted and you will be permitted to lay components in the F1 box. An X will appear in the centre of the board. Note that there are now only two connecting terminals on the centre edges of the board. This is because of the action carried out in step 3. Notice also that in the F3 box, line a is highlighted. This means that you have selected a lumped 50 W resistor to be put on the board. We do not want this; we only want a 50 W transmission line 90° long to be inserted into the system which means that we want to use part b for our 5 Press the F3 key. Press the down arrow key. This will get us to line b. Confirm that this line reads b tline 50 W 90°. If this is not the case, then overtype the line to correct 6 Press the F1 key to return to the Layout box. An X will appear in the centre of the board. If line b of F3 is not already selected, type b to select the 50 W 90° transmission line. 1 Remember the expression for a short-circuited transmission line Z = jZ tan (b l). When b l = 90°, Z = in 0 in infinity; when bl < 90°, Z in is inductive; when bl > 90°, Z in is capacitive. 154 PUFF software Press the left arrow key once, then the down arrow key followed by an = key. Press the up arrow key. This will get you back to the line junction A (not shown on computer screen), press the 1 key. Your construction should now look like the left-hand side of the layout board of Figure 4.6. (If you make any mistake in carrying out these instruc- tions, erase by retracing your step with the shift key pressed down. For example, if you want to erase the horizontal transmission line, press shift+right arrow keys. You can also erase the entire circuit by pressing ctrl+e keys.) 7 Press the right arrow key once; it will now return your cursor to the centre of the board (see junction B of Figure 4.6). Press the down arrow key once and press the = key. This should now give you the centre of Figure 4.6. 8 Press the up arrow key once to return to the centre of the board, press the right arrow key once to get to junction C. See Figure 4.6. Press the down arrow key once and press the = key. Press the up arrow key once; follow by typing the 2 key. You should now get the complete construction of Figure 4.6. 9 Our circuit is now complete and we have put two l/4 sections of 50 W transmission line sandwiched between a 50 W generator and a 50 W load. We also have three short- circuited l/4 lines between junctions A, B, C and ground. We are now in a position to investigate the electrical properties of the filter. 10 Press the F2 key. F2 will now be highlighted and you will be permitted to specify your measurement parameters in the F2 box. 11 Press the down arrow key three times. This will produce a new line X S. 12 Type 21 because we want to measure the parameters S11 and S21. Again refer to Figure 4.6 for guidance. 13 Type p to plot your parameters. You will now get the entire picture of Figure 4.6. 14 If you do not get this figure then repeat the above steps again. 15 To save Figure 4.6, press the F2 key. Type ctrl+s. In the Message box you will see File to save? Type distbpf and press the RETURN key. Figure 4.6 is now saved under the file name distbpf. 4.6.2 Printing and fabrication of artwork If you have the proper printer connected, you should be able to print out the layout for photo-etching purposes to make the actual printed circuit board. The print-out shown in Figure 4.7 is five times the actual physical size of the layout. The magnification of the layout is chosen to reduced the ‘jagged edges’ (constant in a printer) to an insignificant width of the line. The print-out is then photographed and reduced back to the original layout size. In the photographic reduction process, these jagged edges are also reduced by five, so that its effect on the true width of the line is less. The net result is that the line impedance is reproduced more accurately. Note that in the print-out, there is no distinction between the width of the 50 W lines. Ground points are also not shown as these have to be drilled through the board. Do not attempt to print at this time; it will be covered later in the guide. 4.6.3 Summary of Example 4.2 In Example 4.2, you have: Bandpass filter 155 Fig. 4.7 Print-out of a bandpass filter in a 50 Ω system 1 learnt how a bandpass filter can be constructed from l/4 lines; 2 reinforced your ideas of how to use PUFF; 3 read and interpreted the rectangular plot and Smith chart of the bandpass filter intro- duced in a 50 W system; 4 saved another file; 5 understood the artwork for Example 4.2. Self test question 4.1 What do the S11 and S21 rectangular plots (amplitude vs frequency graph) tell you? Answer. The S11 rectangular plot shows that a very good match exists in the passband of the filter and that poor match occurs outside the filter passband. You can check this by pressing the F2 key to enter the plot mode, and by pressing the PageUp and PageDown keys to change the frequency to read S11 at 5 GHz, where the return loss tends toward infinity. You cannot see this on the rectangular plot because, for practical reasons, PUFF reports any magnitude as small as –100 dB as zero and any magnitude greater than 100 dB as zero. At frequencies 3 GHz and 7 GHz, S11 is only about –4 dB. The S21 plot shows 156 PUFF software the transmission plot loss as varying between 0 dB at 5 GHz to about 12 dB at 2 GHz and 8 GHz. 4.7 PUFF commands At this stage, it is becoming increasingly difficult to remember all the commands that you have been shown. To facilitate your work, I have tabulated some commands in Tables 4.1 to 4.4. Table 4.1 F1 box Function right arrow to lay a previously selected component to the right left arrow to lay a previously selected component to the left up arrow to lay a previously selected component above down arrow to lay a previously selected component below 1 to connect a point to connector 1 2 to connect a point to connector 2 3 to connect a point to connector 3 4 to connect a point to connector 4 shift+right arrow to erase a component inserted by the left arrow key shift+left arrow to erase a component inserted by the right arrow key shift+up arrow to erase a component inserted by the down arrow key shift+down arrow to erase a component inserted by the up arrow key shift+e to erase the entire circuit shift+n to move between nodes shift + 1 to move selector to port 1 shift + 2 to move selector to port 2 shift + 3 to move selector to port 3 shift + 4 to move selector to port 4 = to earth a point Table 4.2 F2 box Function p plot ctrl+p plot new modified parameters and keep previous plot page up move measurement up in frequency page down move measurement down in frequency arrow to Points retyping changes number of measurement points arrow to Smith retyping changes radius of Smith chart arrow to S lines to add additional S-parameter measurements TAB toggles Smith chart between Y- and Z-parameters alt+s to toggle an enlarged Smith chart alt+s then TAB toggles an enlarged Smith chart to Y- or Z-parameters ctrl+a prints board artwork on appropriate printer ctrl+s saves file = cursor on Sxx and Smith chart on impedance yields series resistance and reactance of the circuit at port xx = cursor on Sxx and Smith chart on admittance yields parallel resistance and reactance of the circuit at port xx Templates 157 Table 4.3 F3 box Function up arrow move up a line down arrow move down a line right arrow move a space to the right left arrow move a space to the left insert key allows the insertion of characters alt+d inserts the symbol for degrees alt+o inserts the symbol for ohm ctrl+r reads a file j inserts symbol for positive reactance –j inserts symbol for negative reactance S symbol for susceptance mm denotes component size in millimetres M megohms + used for series connections of components, e.g. R + jxx – jxx means resistance + inductance + capacitance in series alt p (//) used when you want components in parallel, e.g. R//jxx//–jxx means resistor, inductance and capacitance are in parallel TAB elongates F3 list to accommodate 18 different components Table 4.4 F4 box Function zd XXX allows change of system impedance fd XXX allow change of central frequency er XXX allows change of board dielectric constant h XXX changes thickness of substrate board s XXX changes size of substrate board c XXX changes distances between connectors TAB toggles layout between microstrip, stripline & Manhattan modes. Microstrip and stripline modes are scaled. Manhattan mode is not scaled but allows PUFF to be used for evaluation and plotting of circuits 4.8 Templates 4.8.1 Introduction At the beginning, we told you that the reason why PUFF is a powerful but relatively small program is because it uses templates to store information. We also asked you to temporar- ily accept the default templates introduced earlier. 4.8.2 Setup templates We are now in a position to show you the default template, setup.puf, which is automati- cally called up when you start up PUFF.2 2 If you want to start up PUFF with a specified template called another, then you must specify it, when you start PUFF by typing PUFF another. PUFF will then start up using the template called another. 158 PUFF software Default template: setup.puf \b{oard} {.puf file for PUFF, version 2.1} d 0 {display: 0 VGA or PUFF chooses, 1 EGA, 2 CGA, 3 One-color} o 1 {artwork output format: 0 dot-matrix, 1 LaserJet, 2 HPGL file} t 0 {type: 0 for microstrip, 1 for stripline, 2 for Manhattan} zd 50.000 Ohms {normalizing impedance. 0<zd} fd 5.000 GHz {design frequency. 0<fd} er 10.200 {dielectric constant. er>0} h 1.270 mm {dielectric thickness. h>0} s 25.400 mm {circuit-board side length. s>0} c 00.000 mm {connector separation. c>=0} r 0.200 mm {circuit resolution, r>0, use Um for micrometers} a 0.000 mm {artwork width correction.} mt 0.010 mm {metal thickness, use Um for micrometers.} sr 0.000 Um {metal surface roughness, use Um for micrometers.} lt 0.0E+0000 {dielectric loss tangent.} cd 5.8E+0007 {conductivity of metal in mhos/meter.} p 5.000 {photographic reduction ratio. p<=203.2mm/s} m 0.600 {mitering fraction. 0<=m<1} \k{ey for plot window} du 0 {upper dB-axis limit} dl –20 {lower dB-axis limit} fl 0 {lower frequency limit in GHZ. fl>=0} fu 10 {upper frequency limit in GHZ. fu>fl} pts 91 {number of points, positive integer} sr 1 {Smith-chart radius. sr>0} S 11 {subscripts must be 1, 2, 3, or 4} S . . . 21 \p{arts window} {O = Ohms, D = degrees, U = micro, |=parallel} lumped 150O tline 50O 90D qline 50O 130D xformer 1.73:1 atten 4dB device fhx04 clines 60O 40O 90D {Blank at Part h } {Blank at Part i } {Blank at Part j } {Blank at Part k } {Blank at Part l } {Blank at Part m } {Blank at Part n } {Blank at Part o } {Blank at Part p } {Blank at Part q } {Blank at Part r } Templates 159 As you can see for yourself, the template contains a lot of information. First and foremost, we shall examine the contents in the default template. Later we will create our own In viewing the template, you will have to constantly refer to the first characters of a line to follow my discussion. \b This line is for identification purposes to enable PUFF to know that it is a template. d The number specifies your display screen. For a VGA screen use 0. o The number specifies the type of printer which you will use to produce the artwork.3 For a bubblejet or deskjet printer try using 1. zd Specifies the normalising impedance of your system. Some antenna systems use 75 normalising impedance. If you use PUFF for other impedances then you must change the value accordingly. fd Specifies the design frequency of your system. Change it if you want a different design frequency. er The bulk dielectric constant of your substrate. Alumina and some Duroids have high dielectric constants. The dielectric constant determines the physical size of your distributed components. Lay your components only on the board with the dielectric constant which you will use in your construction. h Dielectric thickness also affects the physical size of your distributed components. Ensure that your dielectric thickness is that which you will use in your construction. s The square size of your board. The standard default size is 25.4 mm (1 inch square). This is a common size for experimental work but you can choose a size (within limits) to suit yourself. Remember though that your artwork will be several times larger and your printer might not be able to handle it. c The ability to move connector spacing is important because it enables short leads to the connector. r If the distance between components is less than the circuit resolution PUFF will connect the parts together. a Artwork width correction. This is used when you want to alter line width from that calculated from the program. mt The metal thickness is needed for calculating line losses. sr Surface roughness is required for calculating line losses. lt Dielectric loss tangent is also required for calculating line losses. cd Metallic conductivity is also required for calculating line losses. p The photographic reduction ratio used in printing the artwork. You can alter it for greater accuracy but bear in mind your maximum printing size. m Mitreing function is used because when a tx line changes direction or when an open- circuited tx line ends, there is associated stray capacitance. To minimise these effects, corner joints and end joints are frequently ‘thinned’ or mitred. \k Informs PUFF what limits to display on your Smith chart and rectangular plot. du Sets your upper limit in dB (y axis). 3 The reason why I told you not to attempt printing the artwork for the earlier examples is because I have no way of knowing the type (dot-matrix, Laser jet, HPGL file) of your printer. In my case, I have successfully used the Laserjet driver for my Hewlett-Packard bubble-jet printer. Some bubble-jet printers do not respond in this manner and you may be left with half a printed artwork, etc. However, as some of those files were saved, you can print them if you have a printer that will respond to one of the software drivers. 160 PUFF software dl Sets your lower limit in dB (y axis). fl Sets the lower limit in GHz (x axis). fu Sets the upper limit in GHz (x axis). pts Sets the number of points to which you want the circuit calculated and plotted. A larger number gives greater accuracy but takes a longer time. To make your display symmetrical about the centre frequency, you should choose an odd number of sr Determines the Smith chart radius. In most cases you would want a factor of 1, but in oscillator design it is usual to use a Smith chart radius greater than 1. S11 Determines the subscripts you want in your scattering parameter measurements. You can simultaneously measure up to four scattering parameters. \p Informs PUFF that what follows relates to the F3 parts window and that O = ohms, D = degrees, U = micro, | = parallel. lumped 150O = 150 W lumped resistor. tline 50O 90D = 50 W lossless tx line 90° length at centre frequency qline 50O 130D = 50 W lossy tx line 130° length at centre frequency xformer 1.73:1 = transformer with a transformation ratio of 1.73:1 atten 4dB = attenuator with 4 dB attenuation device fhx04 = a transistor called fhx04 whose s-parameters are enclosed clines 60O 40O 90D = coupled lines, one of 60 W, one of 40 W, length = 90° {Blank at Part h} etc. = no parts specified. Note: It is very important that you realise that the template is written in ASCII text and can only be read in ASCII text by PUFF. Do not under any circumstances try to change the default template directly because if you mess it up, PUFF will not run. Follow this proce- 1 always make a copy of the template before altering it; 2 alter the copied template with an ASCII text editor; 3 save your new template in ASCII TEXT. Most DOS provide an ASCII text editor. For example, MSDOS supplies edlin.com for text editing. If you do not have one, then proceed very carefully with a word processor only if it can handle textfiles. Open the template in ASCII text. Make all your changes in ASCII text and save the file in ASCII text. Then and only then will PUFF read the file. When you save a file, PUFF saves the file on a template and includes calculated answers and drawing instructions for the file. You can obtain a full version of it from your distbpf .puf file. I offer an abridged version here for those of you who cannot read the file. Example 4.2 saved template (abridged) \b{oard} {.puf file for PUFF, version 2.1} d 0 {display: 0 VGA or PUFF chooses, 1 EGA, 2 CGA, 3 One-color} o 1 {artwork output format: 0 dot-matrix, 1 LaserJet, 2 HPGL file} t 0 {type: 0 for microstrip, 1 for stripline, 2 for Manhattan} zd 50.000 Ohms {normalizing impedance. 0<zd} fd 5.000 GHz {design frequency. 0<fd} er 10.200 {dielectric constant. er>0} Templates 161 h 1.270 mm {dielectric thickness. h>0} s 25.400 mm {circuit-board side length. s>0} c 19.000 mm {connector separation. c>=0} r 0.200 mm {circuit resolution, r>0, use Um for micrometers} a 0.000 mm {artwork width correction.} mt 0.000 mm {metal thickness, use Um for micrometers.} sr 0.000 Um {metal surface roughness, use Um for micrometers.} lt 0.0E+0000 {dielectric loss tangent.} cd 5.8E+0007 {conductivity of metal in mhos/meter.} p 5.000 {photographic reduction ratio. p<=203.2mm/s} m 0.600 {mitering fraction. 0<=m<1} \k{ey for plot window} du 0 {upper dB-axis limit} dl –20 {lower dB-axis limit} fl 0 {lower frequency limit. fl>=0} fu 10 {upper frequency limit. fu>fl} pts 91 {number of points, positive integer} sr 1 {Smith-chart radius. sr>0} S 11 {subscripts must be 1, 2, 3, or 4} S 21 \p{arts window} {O = Ohms, D = degrees, U = micro, |=parallel} lumped 150O tline 50O 90D qline 50O 130D xformer 1.73:1 atten 4dB device fhx04 clines 60O 40O 90D {Blank at Part h } . . . . . .(abridged) {Blank at Part r } f S11 S21 0.00000 1.00000 –180.0 2.4E–0013 0.0 0.11111 0.99996 177.5 8.7E–0003 87.5 0.22222 0.99985 175.0 1.8E–0002 85.0 0.33333 0.99965 172.5 2.7E–0002 82.5 0.44444 0.99936 169.9 3.6E–0002 79.9 0.55556 0.99896 167.3 4.6E–0002 77.3 . . . abridged 4.00000 2.3E–0002 154.7 0.99974 –115.3 4.11111 4.5E–0002 147.1 0.99897 –122.9 4.22222 5.9E–0002 139.6 0.99826 –130.4 4.33333 6.5E–0002 132.3 0.99790 –137.7 4.44444 6.4E–0002 125.2 0.99794 –144.8 4.55556 5.8E–0002 118.1 0.99832 –151.9 4.66667 4.7E–0002 111.0 0.99888 –159.0 162 PUFF software 4.77778 3.3E–0002 104.0 0.99944 –166.0 4.88889 1.7E–0002 97.0 0.99985 –173.0 5.00000 1.5E–0010 90.2 1.00000 –180.0 5.11111 1.7E–0002 –97.0 0.99985 173.0 5.22222 3.3E–0002 –104.0 0.99944 166.0 5.33333 4.7E–0002 –111.0 0.99888 159.0 5.44444 5.8E–0002 –118.1 0.99832 151.9 5.55556 6.4E–0002 –125.2 0.99794 144.8 5.66667 6.5E–0002 –132.3 0.99790 137.7 5.77778 5.9E–0002 –139.6 0.99826 130.4 5.88889 4.5E–0002 –147.1 0.99897 122.9 6.00000 2.3E–0002 –154.7 0.99974 115.3 . . . abridged 9.00000 0.99588 –156.3 9.1E–0002 –66.3 9.11111 0.99694 –159.2 7.8E–0002 –69.2 9.22222 0.99778 –162.0 6.7E–0002 –72.0 9.33333 0.99844 –164.7 5.6E–0002 –74.7 9.44444 0.99896 –167.3 4.6E–0002 –77.3 9.55556 0.99936 –169.9 3.6E–0002 –79.9 9.66667 0.99965 –172.5 2.7E–0002 –82.5 9.77778 0.99985 –175.0 1.8E–0002 –85.0 9.88889 0.99996 –177.5 8.7E–0003 –87.5 10.00000 1.00000 –180.0 1.5E–0010 –89.9 \c{ircuit} (instructions for layout) 98 0 b 203 2 left 208 3 down 61 3 = 200 2 up 205 1 right 208 4 down 61 4 = 200 1 up 205 5 right 208 6 down 61 6 = 200 5 up From the above two examples, you should now be able to specify a template for different Self test question 4.2 The measurement frequency range for Figure 4.1 is 0–10 GHz. If the measurement frequency range for Figure 4.1 is to be changed from 4.5 to 5.5 GHz, how would you modify the template to measure the frequency range 4.5–5.5 GHz? Modification of transistor templates 163 1 Copy the setup template into an ASCII text editor. 2 Find the line beginning with fl 0. Change the value 0 to 4.5. 3 Find the line beginning with fu 10. Change the value 10 to 5.5. This will make the rectangular plot display its frequency axis as 4.5 to 5.5 GHZ. 4 Save the file in ASCII text format. For ease of explanation, we will call the saved file 5 When you restart PUFF, type PUFF setup1. PUFF will now start using setup1 as the default template. 6 Alternatively, you can start PUFF in the conventional manner. If necessary, press the F3 key to enter the F3 box. Type ctrl+r. You will obtain the reply File to read. Type Alternative method Press F2 key. Press ‘down arrow’ key until cursor is under 0. Overtype 4.5. Next, press ‘down arrow’ key until cursor is under 10. Overtype 5.5. Self test question 4.3 How would you change the amplitude axis of PUFF’s rectangular plot to display an ampli- tude of +20–40 dB? 1 Copy the setup template into an ASCII text editor. 2 Find the line beginning with du 0. Change the value 0 to 20. 3 Find the line beginning with dl –20. Change the value –20 to –40. This will make the rectangular plot display its amplitude axis as 20 to –40. 4 Save the file in ASCII text format. For ease of explanation, we will call the saved file 5 When you restart PUFF, type PUFF setup2. PUFF will now start using setup2 as the default template. Example 4.3 A template is required to make PUFF operate in the range 0–300 MHz and over a dynamic range of 0–40 dB. Make such a template and name it setup300. 1 Copy the setup template into an ASCII text editor. 2 Find the line beginning with dl –20. Move the cursor under the hyphen in 20, type –40. This will make the rectangular plot display its amplitude axis as 0 to –40 dB. 3 Find the line beginning with fu 10. Move the cursor under the 1 in 10, type .3 . This will make the rectangular plot display its frequency axis as 0 to 0.3 GHz. 4 Save the file as setup300 in ASCII text format. 5 Restart PUFF. Type PUFF setup300. PUFF will now start using setup300 as the default Alternative method Press F2 key. Press ‘down arrow’ key until cursor is under –20 posi- tion. Overtype –40. Next, press ‘down arrow’ key until cursor is under 10. Overtype 0.3. 164 PUFF software 4.9 Modification of transistor templates PUFF comes with the template for a HEMT (high electron mobility transistor) called FHX04.dev. It is possible to use other transistor templates provided they are in ASCII text and provided they follow the exact layout for the FHX04.dev detailed below. Again, if you want to make your own template we suggest that you copy the transistor template below and modify it. Template for FHX04.dev {FHX04FA/LG Fujitsu HEMT (89/90), f=0 extrapolated; Vds=2V, Ids=10mA} f s11 s21 s12 s22 0.0 1.000 0.0 4.375 180.0 0.000 0.0 0.625 0.0 1.0 0.982 –20.0 4.257 160.4 0.018 74.8 0.620 –15.2 2.0 0.952 –39.0 4.113 142.0 0.033 62.9 0.604 –28.9 3.0 0.910 –57.3 3.934 124.3 0.046 51.5 0.585 –42.4 4.0 0.863 –75.2 3.735 107.0 0.057 40.3 0.564 –55.8 5.0 0.809 –92.3 3.487 90.4 0.065 30.3 0.541 –69.2 6.0 0.760 –108.1 3.231 75.0 0.069 21.0 0.524 –82.0 7.0 0.727 –122.4 3.018 60.9 0.072 14.1 0.521 –93.6 8.0 0.701 –135.5 2.817 47.3 0.073 7.9 0.524 –104.7 9.0 0.678 –147.9 2.656 33.8 0.074 1.6 0.538 –115.4 10.0 0.653 –159.8 2.512 20.2 0.076 –4.0 0.552 –125.7 11.0 0.623 –171.1 2.367 7.1 0.076 –10.1 0.568 –136.4 12.0 0.601 178.5 2.245 –5.7 0.076 –15.9 0.587 –146.4 13.0 0.582 168.8 2.153 –18.4 0.076 –21.9 0.611 –156.2 14.0 0.564 160.2 2.065 –31.2 0.077 –28.6 0.644 –165.4 15.0 0.533 151.6 2.001 –44.5 0.079 –36.8 0.676 –174.8 16.0 0.500 142.8 1.938 –58.8 0.082 –48.5 0.707 174.2 17.0 0.461 134.3 1.884 –73.7 0.083 –61.7 0.733 163.6 18.0 0.424 126.6 1.817 –89.7 0.085 –77.9 0.758 150.9 19.0 0.385 121.7 1.708 –106.5 0.087 –97.2 0.783 139.1 20.0 0.347 119.9 1.613 –123.7 0.098 –119.9 0.793 126.6 Note that each S-parameter is denoted by an amplitude ratio and angle in degrees. For example at 1 GHz S11 = 0.982 ∠ –20.0° S21 = 4.257 ∠ 160.4° S12 = 0.018 ∠74.8° S22 = 0.620 ∠ –15.2° Self test question 4.4 If you wanted to change the S12 parameter for HEMT FHX04 at 5 GHz to 0.063 31.4, how would you do it? 1 Copy the transistor template (FHX04.dev) into an ASCII text editor. 2 Find the line beginning with 5.0. It should read: 5.0 0.809 –92.3 3.487 90.4 0.065 30.3 0.541 –69.2 3 Change it to read: 5.0 0.809 –92.3 3.487 90.4 0.063 31.4 0.541 –69.2 Verification of some examples given in Chapters 2 and 3 165 4 Save the file in ASCII text format. For ease of explanation, we will call the saved file You can then insert or change this part name in your chosen set-up template so that when- ever you start PUFF, the device will be shown in the F3 box. Alternatively you can insert the part directly into the F3 box whenever you want to use the transistor. 4.10 Verification of some examples given in Chapters 2 and 3 4.10.1 Verification of microstrip line We can now use PUFF to verify some of the conclusions reached in Chapters 2 and 3. In doing so, I will only quote the example number, and where appropriate its question and answer. I will then use PUFF to show that the conclusion is correct. Example 2.3 Two microstrip lines are printed on the same dielectric substrate. One line has a wider centre strip than the other. Which line has the lower characteristic impedance? Assume that there is no coupling between the two lines. Solution. The broader microstrip has the lower characteristic impedance. Using PUFF this is confirmed in Figure 4.8 where the broad microstrip has a characteristic impedance of 20 W and the narrow microstrip has a Z 0 of 90 W. Fig. 4.8 PUFF results showing a 20 Ω microstrip and a 90 Ω microstrip 166 PUFF software 4.10.2 Verification of reflection coefficient Example 2.7 Calculate the reflection coefficient for the case at 5 GHz where Z L = (80 – j10) W and Z 0 = 50 W. ZL − Z0 80 − j10 − 50 30 − j10 Γ= = = ZL + Z0 80 − j10 + 50 130 − j10 31.62 ∠ − 18.43° = = 0.24 ∠ − 14.03° or − 12.305 dB ∠ − 14.03° 130.38 ∠ − 4.40° Solution. Using Equation 2.24 When the above answer is written in dB, we get –12.3 dB ∠ –14.03°. Compare this answer with S11 in the F2 box of Figure 4.9. Fig. 4.9 Verification of S11 for Example 2.7 Example 2.8 Calculate the voltage reflection coefficients at the terminating end of a transmission line with a characteristic impedance of 50 W when it is terminated by (a) a 50 W termination, (b) an open-circuit termination, (c) a short-circuit termination, and (d) a 75 W termination. Given: Z 0 = 50 W, Z L = (a) 50 W, (b) open-circuit = ∞, (c) short-circuit = 0 W, (d) = 75 W. Required: Gv for (a), (b), (c), (d). Verification of some examples given in Chapters 2 and 3 167 Fig. 4.10 Verification of Example 2.8 Solution. Use Equation 2.24. (a) Z L = 50/0° ZL – Z0 50/0° – 50/0° Gv = ——— = —————— = 0/0° 0 dB ZL + Z0 50/0° + 50/0° (b) Z L = open-circuit = ∞ /0° ZL – Z0 ∞ /0° – 50/0° Gv = ——— = —————— = 1/0° = 0 dB ∠ 0° ZL + Z0 ∞ /0° + 50/0° (c) Z L = short-circuit = 0/0° Z L – Z 0 0/0° – 50/0° Gv = ——— = ————— = –1/0° — — or 1/180° = 0 dB ∠ 180° Z L + Z 0 0/0° + 50/0° (d) Z L = 75/0° Z L – Z 0 75/0° – 50/0° Gv = ——— = ————— = 0.2/0° = –13.98 dB ∠ 0° — — Z L + Z 0 75/0° + 50/0° In Figure 4.10, I have plotted case (a) as S11, case (b) as S33,case (c) as S22, case (d) as S44. For S33, I have used a 1000 MW resistor to represent a resistor of infinite ohms. 168 PUFF software Alternatively, you could have used nothing to represent an open circuit. Most r.f. designers do not like open circuits because open circuits can pickup static charges which can destroy a circuit. It is far better to have some very high resistance so that static charges can be discharged to earth. Note how all the answers agree with the calculated ones. 4.10.3 Verification of input impedance Example 2.13 A 377 W transmission line is terminated by a short circuit at one end. Its electrical length is l/7. Calculate its input impedance at the other end. Solution. Using Equation 2.55 2π l ⎡ 2π λ ⎤ Zin = jZ0 tan = j377 tan ⎢ = j377 × 1.254 = j472.8 Ω λ ⎣ λ 7⎥ ⎦ Remembering that l/7 = 51.43° and using PUFF, we see from the Message box that Rs = 0 and Xs = 472.767 W (see Figure 4.11). This confirms the calculated value. Fig. 4.11 Verification of Example 2.13 Verification of some examples given in Chapters 2 and 3 169 Example 2.14 A 75 W line is left unterminated with an open circuit at one end. Its electrical length is l/5. Calculate its input impedance at the other end. Solution. Using Equation 2.56 2π l ⎡ 2π λ ⎤ Zin = jZ0 cot = − j75 cot ⎢ = − j75 × 0.325 = − j24.4 Ω λ ⎣ λ 5⎥ ⎦ Bearing in mind that l/5 = 72° and using 1000 MW to simulate an open circuit, PUFF gives the answer in the Message box as –j24.369 W (see Figure 4.12). Fig. 4.12 Verification of Example 2.14 Example 2.15 A transmission line has a characteristic impedance (Z 0) of 90 W. Its electrical length is l/4 and it is terminated by a load impedance (Z L ) of 20 W. Calculate the input impedance (Z in) presented by the line. Solution. Using Equation 2.57 Z in = (90) 2/20 = 405 W Using PUFF and reading the Message box, we get Rs = 405 W, Xs = 0 W (see Figure 4.13). The above examples should now convince you that much of the transmission line theory covered in Chapter 2 has been proven. 170 PUFF software Fig. 4.13 Verification of Example 2.15 4.11 Using PUFF to evaluate couplers In Section 2.14, we investigated the theory of two popular couplers. These are (a) the branch-line coupler and (b) the rat-race coupler. 4.11.1 Branch-line coupler The theory for the branch-line coupler was covered in Section 2.14.1. For the branch-line coupler, I have used vertical lines with Z 0 of 50 W and horizontal lines with Z 0 of 35.55 W. In the F2 box (Figure 4.14), you can see that the match (S11 to a 50 W system) is excel- lent. S21 and S41 show that the input power from S11 is divided equally between the two ports but that there is a phase change as explained in the text. S31 shows you that there is very little or no transmission to port 3. All the above statements confirm the theory presented in Section 2.14.1. 4.11.2 Rat-race coupler The theory for the rat-race coupler was covered in Section 2.14.3. Here PUFF confirms what we have discussed. In using PUFF, I have chosen Z 0 for the ring as 70.711 W and used a rectangle to represent the ring but all distances between the ports have been kept as before. This is shown in Figure 4.15. Using PUFF to evaluate couplers 171 Fig. 4.14 Verification of the branch-line coupler theory Fig. 4.15 Verification of the rat-race coupler theory 172 PUFF software 4.12 Verification of Smith chart applications In Chapter 3, we used the Smith chart to derive admittances from impedances, calculate line input impedance, and solve matching networks. In this section, we show you how it can also be done with PUFF but note that the intermediate steps in the solutions are not given and sometimes it can be difficult to visualise what is actually happening in a circuit. We shall begin with Example 3.2. As usual we will simply use a numbered example, intro- duce its context and solution and then show how it can be solved with PUFF. 4.12.1 Admittance Example 3.2 Use the Smith chart in Figure 3.6 to find the admittance of the impedance (0.8 – j1.6). Solution. The admittance value is located at the point (0.25 + j0.5). You can verify this yourself by entering the point (0.8 – j1.6) in Figure 3.6. Measure the distance from your point to the chart centre and call this distance d. Draw a line of length 2d from your point through the centre of the chart. Read off the coordinates at the end of this line. You should now get (0.25 + j0.5) S. With PUFF, we simply insert its value in the F3 box, and draw it in the F1 box. In the F2 box, press the TAB key to change the Smith chart into its admittance form. Move the cursor to S11, press p for plot and the equals sign (=) to read its value in the Fig. 4.16 Verification of Example 3.2 Verification of Smith chart applications 173 Message box. Note that Rp and Xp are given as parallel elements and its units are in ohms. However, remembering that (0.25 + j0.5) S is a combination of a conductance of 0.25 S to represent a resistor and j0.5 S to represent a capacitor, we simply take the reciprocal of each element to get the desired answer for each element. This is shown in Figure 4.16. 4.12.2 Verification of network impedances For Example 3.5, we simply draw the network in the F1 box and seek its results in the F2 box and Message boxes. Example 3.5 What is (a) the impedance and (b) the reflection coefficient looking into the network shown in Figure 3.12? Solution. The solution to this problem was given in the annotation to Figure 3.14 as: (a) impedance Z = (0.206 + j0.635) W (b) reflection coefficient G = 0.746 ∠ 113.58° The PUFF solutions (Figure 4.17) give: (a) impedance Z = (0.206 + j0.635) W (b) reflection coefficient G = –2.55 dB ∠ 113.6° which is 0.746 ∠ 113.6° Fig. 4.17 Verification of Example 3.5 174 PUFF software • In Figure 4.17 the drive impedance (zd) in PUFF has to be reduced to 1 W instead of the usual 50 W because the values in the circuit have been normalised. • PUFF only gives the overall input impedance. If you had wanted intermediate values, then you would have to add one immittance at a time and read out its value. 4.12.3 Verification of input impedance of line For this we will use Example 3.6. Example 3.6 A transmission line with a characteristic impedance Z 0 = 50 W is terminated with a load impedance of Z L = (40 – j80) W. What is its input impedance when the line is (a) 0.096l, (b) 0.173l, and (c) 0.206l? Solution. The answers calculated previously are: (a) (0.25 – j0.5) W which after re-normalisation yields (12.5 – j25) W (b) (0.20 – j0.0) W which after re-normalisation yields (10.0 – j0) W (c) (0.21 + j0.2) W which after re-normalisation yields (10.5 + j10) W With PUFF, we obtain: (a) (12.489 – j24.947) W – shown in Figure 4.18. (b) (9.897 + j0.022) W – not shown in Figure 4.18. (c) (10.319 + j10.111) W – not shown in Figure 4.18. Fig. 4.18 Verification of Example 3.6 results Verification of Smith chart applications 175 Items (b) and (c) were obtained from PUFF by moving the cursor in the F2 box to S22 and pressing the = key, and then to S33 and pressing the = key. 4.12.4 Verification of quarter-wave transformers PUFF can be used to investigate the effect of quarter-wave line transformer matching. For this we will use Example 3.11. Example 3.11 A source impedance of (50 + j0) is to be matched to a load of (100 + j0) over a frequency range of 600–1400 MHz. Match the source and load by using (a) one quarter-wave trans- former, and (b) two quarter-wave transformers. Sketch a graph of the reflection coefficient against frequency. Solution. Use Equation 2.57. For the one l/4 transformer, we had previously calculated Z 0t1 as 70.711 W. For the two l/4 transformers, we had previously calculated Z 0t1 as 60 W and Z 0t2 as 84.85 W. We had also obtained the following table. (GHz) 0.6 0.8 1.0 1.2 1.4 One l/4 TX – 13.83 – 19.28 > – 60 – 19.28 – 13.83 Two l/4 TXs 18.81 – 32.09 38.69 32.09 – 18.81 Using PUFF, we show the two results in Figure 4.19. Fig. 4.19 Verification of reflection coefficient using λ/4 line transformers 176 PUFF software 4.13 Verification of stub matching Stub matching is very important. PUFF can be used to match both passive and active networks. To give you an idea of how this is achieved, I will detail the matching of Example 3.12 which was carried out manually in Section 3.8.3. Example 3.12 Use microstrip lines to match a series impedance of (40 – j80) W to 50 W at 1 GHz. 1 Switch on PUFF. Press the F3 key. Type ctrl+r. The program will reply File to read:? 2 Type match1. Press the RETURN key. You will obtain Figure 4.20(a). Note that in the F3 box, we have: • the series impedance we wish to match, (40 – j80); • a transmission line (b) whose length is designated as ?50°; • a transmission line (c) whose length is designated as 50°; • note also that the rectangular plot x axis is marked in degrees and not frequency. The next step is to construct the circuit shown in Figure 4.20(b). 3 Press the F1 key. Type a. Press shift+right arrow key seven times until the cursor is positioned to the right of the layout board. Fig. 4.20(a) Blank matching screen Verification of stub matching 177 Fig. 4.20(b) Second stage of matching 4 Press the down arrow key. Type =. This grounds part a. 5 Press the up arrow key. Type b. Press left arrow key. Type 1. The layout board is now 6 Press the F2 key. Type p. Press the TAB key to change the Smith chart coordinates to an admittance display. You will now obtain Figure 4.20(b). Note that the little square marker is on the lower right of the Smith chart. 7 Type alt+s. You will get an expanded view of the Smith chart similar to that of Figure 8 We now want to move the marker until the square marker intersects the unity circle. Press the page up key several times and the marker will begin to move towards the intersection point with the unity circle. At the same time, look in the F2 box and you will see part b length increasing in degrees. The square marker should reach the unity circle when line b is approximately 38°. At the intersection point, the conductive part of the line is matched to the input, but there is also a reactive part which must be ‘tuned out’. At this stage, we do not know its value but from its chart position, we know that the reactive part is capacitive. 9 Type alt+s to revert back to the display of Figure 4.20(b). 10 Press the F3 key. Use arrow keys to move the cursor to line b and overtype ?50 with 38. You have now fixed line length b at 38°. Use arrow keys to move the cursor to line c and overtype 50 with ?50. See Figure 4.20(d) for both actions. 11 Press the F1 key. Note how line length b has changed. If not already there, use arrow keys to move the cursor until it is at the junction of line 1 and line b. 178 PUFF software Fig. 4.20(c) Intersection point in Smith chart Fig. 4.20(d) Connecting the tuning stub line Verification of stub matching 179 12 Type c to select the other line. To layout line c in the position shown in Figure 4.20(d), press the down arrow key once. Type =. 13 Press the F2 key. Type p. Press the TAB key. You will now get Figure 4.20(d). 14 Type alt+s. You will now obtain the expanded Smith chart shown in Figure 4.20(e) but with the exception that the square marker is on the left edge of the Smith chart. 15 We now want to move the square marker on the unity circle until it reaches the match point in the centre of the Smith chart. Press the page up key several times and the marker will begin to move towards the match point at the centre of the Smith chart. At the same time, look in the F2 box and you will see part c length decreasing in degrees. 16 The square marker should reach the unity circle match point when line c is approxi- mately 29°. Note this length. At the match point, the reactive part will have been ‘tuned out’ by the stub. We can now leave the Smith chart. 17 Summing up: we now know the two line lengths required; line b is 38° and line c is a short-circuited stub of 29°. 18 Press the F3 key. Type ctrl+r. When the program replies File to read? type match6. Press the RETURN key. 19 You will get Figure 4.20(f) where the previously calculated line lengths have been used. Note that the match is best (return loss ≈ 38 dB) at our design frequency of 1 GHz. It is possible to get Figure 4.20(f) directly from Figure 4.20(d). After obtaining and entering line lengths b as 38° and c as 29°, press the F2 key. Press the down-arrow key nine times. Retype over 120 to show 2. Press p and you will obtain the file MATCH6. Fig. 4.20(e) Expanded Smith chart for tuning stub match 180 PUFF software Fig. 4.20(f) Showing the effect of the matching stubs at 1 GHz 4.13.1 Summary of matching methods I would now like to summarise the methods we have used for matching. For easy compar- ison remember that 1 wavelength = 360°, so 29° = 0.081l and 38° = 0.106l. The results for three methods are given in Table 4.5. From the above, you will see that there is little difference whichever method you use. The direct calculations have been found through a ‘goal seek’ program in an Excel spread- sheet. The answers are definitely more accurate, but in practical situations we do not require such accuracy. Also do not worry unduly if you find that when you repeat the same calculations on PUFF your answers may differ slightly (≈0.1 dB). This is due to truncation errors in the program. The graphical methods give an insight into what can be achieved more easily. For exam- ple, in microstrip, a short-circuited stub is not easy to manufacture. In this particular case, we could have increased the length of line b to move the matching point into the inductive part of the Smith chart and then used a capacitive stub for tuning out the inductive part of the circuit. I will not show you how this is done in this example but it is done in Example 4.4 which follows immediately. Table 4.5 PUFF matching Smith chart Direct calculations Example 3.12 (PUFF) Example 3.12 of Chapter 3 Eqn 2.54 l 1 = 38° = 0.106l l 1 = 0.106l l 1 = 0.106 305l Stub = 29° = 0.081l Stub = 0.081l Stub = 0.0 806 036l Verification of stub matching 181 4.13.2 Matching transistor impedances Example 4.4 shows how the input impedance of a transistor (type fhx04) can be matched to 50 W at 5 GHz. In this example, I will only provide you with intermediate diagrams because the methodology is identical to that of Example 3.12. Two methods are shown: • a capacitive stub matching system shown in Figures 4.21(a) to (d); • an inductive stub matching system shown in Figures 4.22(a) to (c). Either method is suitable, but in microstrip circuits it is much easier to make an open- circuited stub than a short-circuited stub; therefore the capacitive stub matching method is preferred. However, you should compare Figure 4.21(d) and Figure 4.22(c) and note that although matching is achieved at our desired frequency of 5 GHz, there are matching differences on ‘off-frequency’ matching. If you wish to try these matching networks out for yourself, Figures 4.21(a) to (d) are given as files sweep1 to sweep4 respectively on your disk. Figures 4.22(a) to (c) are given on your disk as files sweep22, sweep33 and sweep44 respectively. As before, I suggest that you start off with Figure 4.21(a) and build up the capacitive stub matching system. This ensures that if you run into trouble, you will have the other templates available. Similarly, start off with Figure 4.22(a) for the inductive stub matching system and build up the circuit accordingly. Transistor matching using a capacitive stub Fig. 4.21(a) First matching line 182 PUFF software Fig. 4.21(b) Determining first matching line length for a capacitive stub Fig. 4.21(c) Determining length of a capacitive tuning stub Verification of stub matching 183 Fig. 4.21(d) Matching using a capacitive stub Transistor matching using an inductive stub Fig. 4.22(a) Determining first matching line length for an inductive matching stub 184 PUFF software Fig. 4.22(b) Determining length of an inductive tuning stub Fig. 4.22(c) Matching at 5 GHz using an inductive stub Verification of stub matching 185 Verification of output impedance matching If you want to match the output impedance of any active or passive device use similar procedures to that of Example 4.4. The detailed matching procedure is again identical to Example 3.12. 4.13.3 Stub matching second example Here is another example of stub matching. Try to see if you can carry out the stub match- ing for Example 3.13 which was done manually in Chapter 3. Example 3.13 A transistor amplifier has an h.f. input resistance of 100 W shunted by a capacitance of 5 pF. Find the length of short-circuit stub, and its position on the line, required to match the amplifier input to a 50 W line at 1 GHz. • The stub connection point is 0.028l from the transistor input. • The short-circuit stub length is 0.065l at the connection point. Example 3.13 is another example of stub matching. You already know the answer. See if you can use PUFF to match the circuit on your own. Hint: if you cannot do it, look at Figure 4.23. Fig. 4.23 Verification of Example 3.13 186 PUFF software 4.13.4 Double stub tuning verification PUFF can also be used for verifying double stub matching. We will use Example 3.14 which was carried out manually in Chapter 3. Example 3.14 A system similar to the double stub matching system shown in Figure 3.16 has a load Z L = (50 + j50) W which is to be matched to a transmission line and source system with a char- acteristic impedance of 50 W. The distance, d 1, between the load and the first stub is 0.2l (72°) at the operating frequency. The distance, d 2, between the two stubs is 0.125l (45°) at the operating frequency. Use a Smith chart to estimate the lengths l1 and l 2 of the stubs. Solution. In Example 3.14, we found that: • stub 1 required an electrical length of 0.167l or 60.12°; • stub 2 required an electrical length of 0.172l or 61.92°; The construction using PUFF is shown in Figure 4.24. Fig. 4.24 Verification of Example 3.14 4.14 Scattering parameters PUFF can also be used for calculating S-parameters. We demonstrate this with Examples 3.15, 3.16 and 3.17. Scattering parameters 187 4.14.1 Series elements Example 3.15 Calculate the S-parameters for the two-port network shown in Figure 3.30 for the case where Z 0 = 50 W. Solution. Summing up for S-parameters: S11 = 0.333 ∠ 0° or –9.551 dB ∠ 0° S12 = 0.667 ∠ 0° or –3.517 dB ∠ 0° S21 = 0.667 ∠ 0° or –3.517 dB ∠ 0° S22 = 0.333 ∠ 0° or –9.551 dB ∠ 0° This circuit is shown in Figure 4.25. Fig. 4.25 Verification of Example 3.15 4.14.2 Shunt elements PUFF can be used to calculate shunt elements as shown in Example 3.16. Example 3.16 Calculate the S-parameters for the two port network shown in Figure 3.32 for the case where Z 0 = 50 W. Solution. Summing up for S-parameters: S11 = 0.333 ∠ 180° or –9.551 dB ∠ 180° S12 = 0.667 ∠ 0° or –3.517 dB ∠ 180° S21 = 0.667 ∠ 0° or –3.517 dB ∠ 180° S22 = 0.333 ∠ 180° or –9.551 dB ∠ 180° 188 PUFF software Fig. 4.26 Verification of Example 3.16 The values calculated by PUFF are shown in Figure 4.26. You can see that they are 4.14.3 Ladder network PUFF can be used for calculating ladder networks. This is shown by Example 3.17 which was carried out manually in Chapter 3. Example 3.17 (a) Calculate the S-parameters for the two-port network shown in Figure 3.32 for the case where Z 0= 50 W. (b) Find the return loss at the input with Z L = Z 0. (c) Determine the insertion loss for the network when the generator and the termination are both 50 W. Solution. To sum up for S-parameters (a) S11 = 0.518 ∠ 131.16° or –5.713 dB ∠ 131.16° S12 = 0.524 ∠ –16.22° or –5.613 dB ∠ –16.22° S21 = 0.524 ∠ –16.22° or –5.613 dB ∠ –16.22° S22 = 0.442 ∠ 172.87° or –7.092 dB ∠ 131.16° Discontinuities: physical and electrical line lengths 189 Fig. 4.27 Verification of Example 3.17 (b) From part (a), G ∠ q = 0.518 ∠ 131.16°. Hence return loss (dB) = –20 log10 |0.518| = –20 × (–0.286) = 5.71 dB (c) The forward power gain of the network will be |S21| 2. |S21| 2 = (0.524)2 = 0.275 This represents a loss of –10 log10 0.275 = 5.61 dB. Figure 4.27 gives the answers for the parameters. To derive the other two answers, namely (b) return loss and (c) forward power, you merely read off S11 and S21 and calculate to get the values. 4.15 Discontinuities: physical and electrical line lengths This section is vitally important in the construction of your circuits. In all the problem solving given earlier, the theoretical (electrical) line length has been assumed. In other words, we have taken a physical line length of one wavelength and assumed it to be 360 electrical degrees. In the practical case, if you were to do this with a transmission line, you would find that a physical length of one wavelength is not likely to be 360 electrical 190 PUFF software Fig. 4.28 Effect of fringing fields in transmission lines degrees. This is due to end effects and line fringing effects, shown in Figure 4.28. The general name for these effects is discontinuities. PUFF does not take these effects into account when drawing the artwork; therefore you must compensate for them when you use PUFF to draw the artwork. UCLA (PUFF program writers)1 suggest that we consider four dominant discontinuities in microstrip. These are: • excess capacitance of a corner; • capacitive end effects for an open circuit; • step change in width; • length correction for the shunt arm of a tee junction. 4.15.1 Excess capacitance of a corner When a sharp right-angle bend occurs in a circuit (Figure 4.29(a)) there will be a large reflection from the corner capacitance. PUFF mitres corners to reduce the capacitance and minimise this reflection as shown in Figure 4.29(b). You can change the value of the mitre fraction (m) set in the setup.puf template as 0.6. The mitre fraction (m) is defined as: m = 1− b w1 + w2 (4.1) Fig. 4.29 Chamfering (mitreing) of corners 1 This is also on the CD-ROM PUFF manual. Discontinuities: physical and electrical line lengths 191 Fig. 4.30 Line length compensation for end effects 4.15.2 Capacitance end effects for an open circuit In an open-circuit line, the electric fields extend beyond the end of the line. This excess capacitance makes the electrical length longer than the nominal length of the line, typically by a third to a half of the substrate thickness. To compensate for this effect in the artwork, a negative length correction can be added to the parts list. Hammerstad and Bekkadal4 give an empirical formula for the length extension l in microstrip: l ⎛ ε + 0.3 ⎞ ⎛ w h + 0.262 ⎞ = 0.412⎜ eff ⎟⎜ ⎟ (4.2) h ⎝ ε eff − 0.258 ⎠ ⎝ w h + 0.813 ⎠ where eeff is the effective dielectric constant of the through arm. Note: In the above correction, the length l must be negative, i.e. the length l must be subtracted from the desired length in the parts list. 4.15.3 Step change in width of microstrip A similar method may be used to compensate for a step change in width between high and low impedance lines. This is shown in Figure 4.31. The discontinuity capacitance at the end of the low impedance line will have the effect of increasing its electrical 4 E.O. Hammerstad and F. Bekkadal, A Microstrip Handbook, ELAB Report, STF 44 A74169, N7034, University of Trondheim, Norway, 1975. 192 PUFF software Fig. 4.31 Step change in width of microstrip Assuming the wider low impedance line has width w2, and the narrow high impedance line has width w1, compensate using the expression suggested by Edwards5 ls ⎛ ε + 0.3 ⎞ ⎛ w h + 0.262 ⎞ ⎡ w1 ⎤ = 0.412⎜ eff ⎟⎜ ⎟ ⎢1 − ⎥ (4.3) h ⎝ ε eff − 0.258 ⎠ ⎝ w h + 0.813 ⎠ ⎣ w2 ⎦ ls l ⎡ w1 ⎤ = ⎢1 − ⎥ (4.3a) h h ⎣ w2 ⎦ where ls is the step length correction for line w2 and l/h is the value obtained from Equation 4.2 and Figure 4.30. 4.15.4 Length correction for the shunt arm of a tee-junction In the tee-junction shown in Figure 4.32, the electrical length of the shunt arm is short- ened by distance d 2. The currents effectively take a short cut, passing close to the corner. It is particularly noticeable in the branch-line coupler because there are four tee- Fig. 4.32 Length correction for the shunt arm of a tee-junction 5 T.C. Edwards, Foundations for microstrip circuit design, second edition, John Wiley & Sons, ISBN 0 471 93062 8, 1992. Summary 193 junctions. Hammerstad and Bekkadal (see footnote 4) give an empirical formula for d 2 in microstrip: d2 120π ⎧ Z1 ⎫ = ⎨0.5 − 0.16 [1 − 2 ln( Z1 Z2 )]⎬ (4.4) h Ζ 1 ε eff ⎩ Z2 ⎭ where εeff is the effective dielectric constant of the through arm. Equation 4.4 is plotted in Figure 4.32 for a 50 W through line. Additional help on discontinuity modelling for both microstrip and stripline can be found in a book by Gupta.6 4.16 Summary By now, I am sure you will agree that your studies in Parts 2 and 3 on transmission lines, Smith charts and S-parameters are beginning to bring rewards and help you toward the goal of being a good h.f. and microwave engineer. Sections 4.1 to 4.3 of this part have been devoted to the installation of PUFF. In Section 4.4, we covered the principles of using PUFF. Section 4.5 provided some simple examples of how to use the facilities provided by PUFF for printing and production of artwork. In Section 4.6, we designed and produced the artwork, and measured the frequency response of a bandpass filter using transmission lines. Section 4.7 was used to collect and collate all the PUFF commands that you had learnt previously. The use, design and modification of templates for the PUFF system were discussed in Section 4.8. In Section 4.9, we learnt how to manipulate and alter transistor templates for PUFF. In Section 4.10, we achieved our goal of verifying and checking that the work carried out in Parts 2 and 3 was valid. Fifteen examples (2.3, 2.7, 2.8, 2.13, 2.14, 2.15, 3.2, 3.5, 3.6, 3.11, 3.12, 3.13, 3.14, 3.15, 3.16 and 3.17) were entered into PUFF. Their results were compared with the examples produced manually in Parts 2 and 3. The fact that both sets of results agree should give you confidence in the use of either method. In Section 4.11, we used PUFF to investigate the properties of the branch-line coupler and the rat-race coupler. We evaluated their transmission and matching properties. Section 4.12 was used to show how PUFF can be used to find admittances (Example 3.2), network impedance and reflection coefficient (Example 3.5), input impedance of transmission lines (Example 3.6), quarter-wave transformers (Example 3.11), and cascad- ing of quarter-wave transformers. The examples created manually in Part 3 all agree with the solutions provided by PUFF. The very important technique of stub matching was detailed and demonstrated in Section 4.13. It provided details on how single stub matching can be carried out with PUFF. The PUFF answer agreed well with Example 3.12 which was previously carried out manually and also with direct calculations. See Table 4.5 in Section 4.13.1 for details. Section 4.13.2 provided details on how matching can be carried out using inductive or capacitive tuning stubs. Section 4.13.3 provided an electronic matching of Example 3.13. Double stub electronic matching of Example 3.14 was verified in Section 4.13.4. 6 K.C. Gupta, R. Garg and R. Chadha, Computer-aided design of microwave circuits, Artech House, Deham, Mass. USA, ISBN 0–89006–105–X, 1981. 194 PUFF software Section 4.14 demonstrated how PUFF can be used to calculate the S-parameters of series elements (Example 3.15), shunt elements (Example 3.16) and networks (Example The important subject of discontinuities in microstrip and how they may be compen- sated for in the PUFF artwork was covered in Section 4.15. Four types were discussed, and compensation methods for minimising these effects were shown. Now that you are familiar with many passive networks and their solutions, we will be moving on to active circuits, mainly the design of amplifiers, in the following parts. However, this is not the last of PUFF because we will be using it in the design of filters and amplifiers. Last but not least, the use of PUFF in the design and layout of circuits detailed in an article called ‘Practical Circuit Design’ is reproduced on the disk accompanying this book. However, I advise you to defer reading it until you have reached the end of Part 7 because many of the principles and techniques used in the article have yet to be explained. Amplifier basics 5.1 Introduction The information gained in the previous parts has now allowed us to move into the realms of amplifier design. Small signal r.f. amplifiers assume many configurations. We show two common configurations. In Figure 5.1, we show the circuit of a single stage amplifier. It consists of five main sections: • input source with a source impedance Z s; • an input tuned/matching circuit comprising C1, L1 and C 2; • a transistor amplifier (transistor biasing is not shown); • an output tuned/matching circuit comprising L 2 and C 3; • load (Z L). In Figure 5.2, we show the circuit of a multi-stage integrated amplifier circuit. It consists of five main sections: • input source with a source impedance Z s; • a multi-stage amplifier gain block (sometimes called ‘gain blok’); Fig. 5.1 Single stage amplifier 196 Amplifier basics Fig. 5.2 Multi-stage amplifier • a multi-tuned/matching filter circuit comprising C1, L 1, C 2, L 2 and C3; • a multi-stage amplifier gain block (sometimes called ‘gain blok’); • load (Z L). From the above figures, it is clear that to design a circuit, we must understand: • tuned circuits • filters • matching techniques • amplifier parameters • gain block parameters Much material will be devoted to matching circuits in this chapter because after selection of a transistor or gain block for a particular design, there is not much you can do within the active device other than present efficient ways in which energy can be coupled in and out of the device. This in turn calls for efficient matching circuits for the intended In this chapter, we will investigate tuned circuits, filters and impedance matching tech- niques. This will enable us to deal with transistors, and semiconductor devices in the next 5.1.1 Aims The aims of this chapter are to introduce you to the passive elements and/or devices which are used in conjunction with active devices (transistors, etc.) to design complete circuits. 5.1.2 Objectives The objectives of this chapter are to show how passive, discrete and distributed elements can be used in the design of tuned circuits, filters and impedance matching networks. 5.2 Tuned circuits As these equations are readily available in any elementary circuit theory book, we shall simply state the equations associated on single series and parallel tuned circuits. Tuned circuits 197 5.2.1 Series circuits The series C, L and R circuit is shown in Figure 5.3. The fundamental equations relating to the series circuit are: Z = R + jωL + 1 ( jωC ) − (5.1) ωo = 1 LC (5.2) vr R = (5.3) vs R + j (ωL − 1 ωC ) Q = ωoL R or 1 (ω o CR) (5.4) Q = ω o (ω 2 − ω1 ) (5.5) Z = input impedance with R (ohms), L (Henries), C (Farads) wo = resonant frequency in radians per second vr = voltage across resistor R vs = open-circuit source voltage Q = quality factor w2 = upper frequency (rads/sec) where the response has fallen by 3 dB w1 = lower frequency (rads/sec) where the response has fallen by 3 dB w2 – w1 = 3 dB bandwidth of the circuit Fig. 5.3 Series circuit Example 5.1 A series CLR circuit has R = 3 W, L = 20 nH and a resonant frequency ( f0) of 500 MHz. Estimate (a) its impedance at resonance, (b) the value of the capacitance needed for reso- nance at 500 MHz, (c) Q of the circuit at resonance, and (d) the 3 dB bandwidth. Given: R = 3 W, L = 20 nH and f 0 = 500 MHz. Required: (a) Impedance at resonance, (b) value of series capacitance for resonance at 500 MHz, (c) Q of the circuit at resonance and (d) the 3 dB bandwidth of the circuit. (a) Using Equation 5.1 Z = R + jwL + (1/( jwC) = 3 + j(X L) – j(XC) 198 Amplifier basics Since XL = XC at resonance (b) Using Equation 5.2 ωo = 1 LC = 2π × 500 MHz = (20 nH × C pF) −0.5 C = 5.066 pF (c) Using Equation 5.4 Q = woL/R or 1/(woCR) = (2p × 500 MHz × 20 nH)/3 = 62.832/3 = 20.944 (d) Using Equation 5.5 Q = wo/(w2 – w1) Therefore 20.944 = 500 MHz/bandwidth MHz. Hence 3 dB bandwidth ≈ 23.873 MHz Using PUFF To find C, we invoke the simple optimiser in PUFF which is called the component sweep. Instead of sweeping with frequency, a circuit’s scattering parameters may be swept with respect to a changing component parameter. This feature is invoked by placing a question mark (?) in front of the parameter to be swept in the appropriate position of a part description in the F3 box. This is shown in Figure 5.4 where a question mark (?) has been placed in front Fig. 5.4 Using PUFF to sweep-change the value of C Tuned circuits 199 Fig. 5.5 Equivalent circuit used by PUFF of the 10 pF in the F3 box.1 PUFF now knows that we wish to sweep-change the value of C until we get resonance at the fd frequency which has been set to 0.5 GHz or 500 MHz in the F4 box. If you now press the F2 key and press the p key, you will get the plot shown in Figure 5.4. Note that in the third sentence in the F2 box, we have the Part b 5.0625 pF. You will not get this value initially, because the first displayed value is not in resonance; however, if while in the p plot mode, you press the page up and/or page down keys, you will find the value of Part b changing. You will also see the X mark on the rectangular plot move simultaneously. Keep pressing the page up or page down keys, until S11 shown in the F2 box is reading the largest negative number, in this case, S11 ≈ –67 dB. Now Part b will show 5.06 pF approximately. This is the value of C which will resonate with the 20 nH to produce resonance at 500 MHz. The reason why I have asked you to use the S11 indicator rather than the S21 indicator is because it is easier to locate the minimum point. This is best explained by Figure 5.5 where I have shown the equivalent circuit used by PUFF. You know that you only get perfect match (S11 = 0) when Z d (source) is terminated by Zd (load). This will only occur when j(wL – 1/wC) = 0. Having found the value of C as 5.06 pF, we can now plot the circuit conventionally and obtain the response of Figure 5.6. To obtain better scaling in Figure 5.6, I have copied and modified the PUFF set-up template and changed the frequency range from 400 MHz to 600 MHz, fd to 500 MHz and Zd to 1.5 W so that the total resistance in the circuit is 1.5 W + 1.5 W (see Figure 5.5), i.e. 3 W. If we now press the F2 key and p, we will get the response of the Q curve and by using the page up and page down keys, we can observe that the upper –3 dB point occurs at approximately 512.5 MHz. The low –3 dB point occurs at 488.5 MHz. Hence the 3 dB bandwidth is (512.5 – 488.5) MHz = 24 MHz. To sum up: Item Calculation PUFF Value of capacitance 5.066 pF 5.0625 pF 3 dB bandwidth 23.873 MHz 24 MHz You may well ask whether doing it by PUFF is worth the effort when you can obtain good results by calculation. It is worth it, because PUFF gives you a picture of the circuit 1 Swept lumped components are restricted to single resistors, capacitors or inductors. A description such as lumped ?1+5j–5j W is not allowed since it is a series CLR circuit. In addition the parallel sign | | cannot be used in the lumped specification. The unit and prefix given in the part description (following the ?) is inherited by the component sweep. 200 Amplifier basics Fig. 5.6 Response of tuned circuit response. It tells you the amount of rejection (attenuation) for frequencies outside the reso- nance frequency. It also shows you how the Q must be modified to get the results you want. Last, but not least, using PUFF gives you confidence for more complicated circuits later in the book. 5.2.2 Parallel circuits Similar results can also be obtained either by calculation or by using PUFF for parallel circuits which are normally used for the load impedance of amplifiers. The fundamental equations relating to the parallel circuit are: Z=1 Y (5.6) Y = G + jwC – j(1 wL) (5.7) ωo = 1 LC (5.8) ir G = (5.9) is G + jωC − j1 ωL Q = R wo L or w oCR (5.10) Q = wo (w 2 – w1) (5.11) Tuned circuits 201 Z = input impedance with R (ohms), L (henries), C (farads) Y = input admittance with G (Siemens), L (henries), C (farads) wo = resonant frequency in radians per second ir = current across conductance G is = total current through admittance Q = quality factor w2 = upper frequency (rads/sec) where the response has fallen by 3 dB w1 = lower frequency (rads/sec) where the response has fallen by 3 dB w 2 – w1 = 3 dB bandwidth of the circuit Example 5.2 A parallel circuit (Figure 5.7) consists of an inductor of 20 nH, a capacitance of 5.06 pF and a resistance across the tuned circuit of 2.5 kW. It is driven from a current source. Plot its frequency response from 400 MHz to 600 MHz. Fig. 5.7 Parallel tuned circuit Solution. Using PUFF, we obtain Figure 5.8. In the F3 box, we have used a symbol | | which signifies that two elements are in parallel and changed the scaled microstrip lines in the F4 box to the Manhattan mode. The Manhattan mode allows PUFF to carry out calcu- lations without bothering about the physical size of components. In the F4 box, I have also set Zd to 5000 W and, bearing in mind Figure 5.7, it is readily seen that this is equivalent to having a combined resistance of 2.5 kW across the tuned circuit. From Figure 5.8, the –3 dB bandwidth of the circuit is measured to be (506.5 – 494.0) MHz or 12.5 MHz. The Q of the circuit is 500 MHz/12.5 MHz = 40. 5.2.3 Cascading of tuned circuits Most radio frequency systems use a number of tuned circuits in cascade to achieve the required selectivity (tuning response). One such arrangement commonly used in broadcast receivers is shown in Figure 5.9. You should note that amplifiers are placed in between the tuned circuits so that they do not interact directly with each other. One way would be to derive the response of each individual tuned circuit, then multi- ply their individual responses to obtain the overall response. Another way would be to take the individual responses in dB and add them together. I have done this for you. The 202 Amplifier basics Fig. 5.8 Frequency response of a parallel tuned circuit calculations are shown in Table 5.1. The results can then be plotted as shown in Figure 5.10. Although there are two tuned circuits each with a Q of 35, I have only plotted one for the sake of clarity. You should also note that the frequency scale (w/wo) has been plot- ted linearly this time instead of logarithmic. This is to allow a better view of the response near the resonant frequency. Q = 15 Fig. 5.9 Tuned circuit arrangement of a broadcast radio receiver Filter design 203 Table 5.1 Q factor responses Fractional frequency (rad/s) Attenuation is given in dB w/wo Q = 15 Q = 35 Q = 35 Total Q 0.85 –13.98 –21.19 –21.19 –56.4 0.9 –10.42 –17.45 –17.45 –45.3 0.93 –7.595 –14.29 –14.29 –36.2 0.95 –5.276 –11.43 –11.43 –28.1 0.97 –2.637 –7.441 –7.441 –17.5 0.98 –1.359 –4.772 –4.772 –10.9 0.99 –0.378 –1.746 –1.746 –3.9 0.995 –0.097 –0.504 –0.504 –1.1 1.0 0.0 0.0 0.0 0.0 1.005 –0.096 –0.5 –0.5 –1.1 1.01 –0.371 –1.718 –1.718 –3.8 1.015 –0.79 –3.194 –3.194 –7.2 1.02 –1.313 –4.656 –4.656 –10.6 1.05 –4.975 –11.03 –11.03 –27.0 1.08 –8.022 –14.78 –14.78 –37.6 1.11 –10.35 –17.37 –17.37 –45.1 1.13 –11.62 –18.72 –18.72 –49.1 1.15 –12.72 –19.88 –19.88 –52.5 1.18 –14.13 –21.35 –21.35 –56.8 Fig. 5.10 Graph of the r.f. response curve of a broadcast radio receiver 5.3 Filter design I will now refer you to Figure 5.2 where filters are interspersed between amplifiers to determine the frequency response of an amplifier block. We will commence by discussing the main types of filters and later provide details of how these can be designed. 204 Amplifier basics 5.3.1 Introduction Figure 5.11 shows a multi-element low pass filter which is used at low frequencies. As frequency increases, the circuit elements C1, L 2, C3, L4 and C5 decrease and at microwave frequencies these element values become very small. In fact, in many cases, these calcu- lated values are simply too small in value to implement as lumped elements and transmis- sion line elements are used to provide the equivalent. Such a microstrip filter is shown in Figure 5.12. Comparing the two figures, it can be seen that capacitors are represented by low imped- ance lines while inductors are represented by high impedance lines. You should not be surprised by this innovation because in Section 2.13.3 we have already shown you how transmission lines can be used to construct inductors and capacitors. Fig. 5.11 Low pass filter Fig. 5.12 Microstrip low pass filter An example of how a high pass filter (Figure 5.13) can be implemented in microstrip line is shown in Figure 5.14. In this case similar microstrip type configurations are used to represent inductors and capacitors. Fig. 5.13 High pass filter Filter design 205 Fig. 5.14 Microstrip high pass filter Finally in Figures 5.15 and 5.16, we show how coupled filter circuits can be constructed in microstrip configuration. Fig. 5.15 Coupled tuned circuits Fig. 5.16 Microstrip coupled circuits In general, most microwave filters are first designed as conventional filters and then the calculated values are translated into microwave elements. In the above figures, we have only shown microstrip filters but there is no reason why microwave filters cannot be made in other configurations such as transmission lines and waveguides. Microstrip lines are more popular because they can be made easily and are relatively cheap. 5.3.2 Overview of filters In this section we will show you how to select and design various types of multi-element filters for dedicated purposes. Once these methods have been learnt then it becomes comparatively easy to design microwave filters. Hence the following sections will concen- trate on: • formulating your filter performance requirements; • deciding which type of filter network you need to meet these requirements; • calculating or finding out where the normalised element values are published; • performing simple multiplication and/or division to obtain the component values. 206 Amplifier basics 5.3.3 Specifying filters The important thing to bear in mind is that although the discussion on filters starts off by describing low pass filters, we will show you later by examples how easy it is to change a low pass filter into a high pass, a bandpass or a bandstop filter. Figure 5.17(a) shows the transmission characteristics of an ideal low pass filter on a normalised frequency scale, i.e. the frequency variable (f) has been divided by the pass- band line frequency ( fp). Such an ideal filter cannot, of course, be realised in practice. For a practical filter, tolerance limits have to be imposed and it may be represented pictorially as in Figure 5.17(b). Fig. 5.17 (a) Ideal filter Fig. 5.17 (b) Practical filter The frequency spectrum is divided into three parts, first the passband in which the inser- tion loss (A p) is to be less than a prescribed maximum loss up to a prescribed minimum frequency ( fp). The second part is the transition limit of the passband frequency limit fp and a frequency Ws in which the transition band attenuation must be greater than its design attenuation. The third part is the stopband limit in which the insertion loss or attenuation is to be greater than a prescribed minimum number of decibels. Hence, the performance requirement can be specified by five parameters: • the filter impedance Z 0 • the passband maximum insertion loss (A p) • the passband frequency limit ( fp) • the stopband minimum attenuation (A s) • the lower stopband frequency limit (Ws) Filter design 207 Table 5.2 Equivalence between reflection coefficient, RLR, Ap and VSWR Maximum reflection Minimum return loss Maximum passband Zout coefficient r% ratio RLR(dB) insertion loss VSWR = —— Ap (dB) Zin 1 40 0.00043 1.020 1.7 35 0.001 1.033 2 34 0.0017 1.041 3 30 0.0043 1.062 4 28 0.007 1.083 5 26 0.01 1.105 8 22 0.028 1.174 10 20 0.043 1.222 15 16 0.1 1.353 20 14 0.18 1.50 25 12 0.28 1.667 33 10 0.5 1.984 45 7 1 2.661 50 6 1.25 3 61 4.3 2 4.12 71 3 3 5.8 Sometimes, manufacturers prefer to specify passband loss in terms of return loss ratio (RLR) or reflection coefficient (r). We provide Table 5.2 to show you the relationship between these parameters. If the values that you require are not in the table, then use the set of formulae we have provided to calculate your own values. These parameters are inter-related by the following equations, assuming loss-less reac- RLR = –20 log |r| (5.12) Ap = 10 log (1 – | r|2) (5.13) Zout 1 + |r| VSWR = —— = ———— (5.14) Z in 1 – | ρ| 5.3.4 Types of filters There are many types of filter. The more popular ones are: • Butterworth or maximally flat filter; • Tchebyscheff (also known as Chebishev) filter; • Cauer (or elliptical) filter for steeper attenuation slopes; • Bessel or maximally flat group delay filter. All of these filters have advantages and disadvantages and the one usually chosen is the filter type that suits the designer’s needs best. You should bear in mind that each of these filter types is also available in low pass, high pass, bandpass and stopband configurations. We will discuss in detail the Butterworth and the Tchebyscheff filters. 208 Amplifier basics Fig. 5.18 Butterworth filter 5.4 Butterworth filter Figure 5.18 shows the response of the maximally flat, power law or Butterworth type which is used when a fairly flat attenuation in the passband is required. The Butterworth filter achieves the ideal situation only at the ends of the frequency spectrum. At zero frequency the insertion loss is zero, at low frequencies the attenuation increases very grad- ually, the curve being virtually flat. With increasing frequency the attenuation rises until it reaches the prescribed limit. At the 3 dB frequency there is a point of inflexion, and thereafter the cut-off rate increases to an asymptotic value of 6n dB/octave, where n is the number of arms. As the number of arms is increased the approximation to the ideal improves, the passband response becomes flatter and the transition sharper. For instance, for 3, 5 and 7 arms, the 1 dB loss passband frequencies are 0.8, 0.875 and 0.91 respectively of the 3 dB frequency, and the corresponding 40 dB frequencies are 4.6, 2.6 and 1.9 times the 3 dB For values of As greater than 20 dB and RLR greater than 10 dB, you can use Equation 5.15 to calculate the number of arms (n) required in the filter for a given attenuation at a given frequency: A s + RLR n = ———— — (5.15) [20 log Ws] Alternatively if you prefer, you can use the ABAC of Table 5.3 to get the same result. To use the ABAC, simply lay a ruler across any two parameters and read the third parameter. This is best demonstrated by an example. Example 5.3 A low pass Butterworth filter is to have a cut-off frequency of 100 MHz. At 260 MHz, the minimum attenuation in the stopband must be greater than 40 dB. Estimate the number of arms required for the filter. Solution. In terms of normalised units (Ws), 260 MHz/100 MHz = 2.6. Using Equation Butterworth filter 209 As + RLR 40 n= = = 4.82 ≈ 5 arms 20 log Ωs 20 log 2.6 Alternatively, using the ABAC of Table 5.3 and drawing a straight line between 40 on the left and 2.6 on the right will also give an answer of n < 5 arms. Table 5.3 ABAC for estimating the number of arms required for a given return loss and attenuation 210 Amplifier basics 5.4.1 Normalised parameters Each type of filter also has one or more sets of normalised parameters which are used for calculating its component values. Normalised parameters are values which a low pass filter would assume for its components if it was designed for (i) 1 W termination and (ii) an oper- ating angular frequency of 1 rad/s. The reason for choosing 1 W and 1 rad/s is that it enables easy scaling for different filter impedances and operating frequencies. Another point you should note about Figure 5.19 is that the same configuration can be used for a high pass filter by simply interchanging L with C, etc. Bandpass and bandstop filters can also be produced in this manner. We shall carry out all these manipulations later in the design examples. Fig. 5.19 Schematic of a Butterworth normalised low pass filter The set of normalised parameters for a Butterworth filter can be calculated from Equation 5.16: gk = 2 sin [ (2k – 1)p 2n ] (5.16) k = position of element in array [k = 1, 2, 3, . . ., n – 1, n] n = number of elements for the filter Note: Before you take the sine value, check that your calculator is set to read radians. To save you the problem of calculating values, we attach a set of values calculated on a spreadsheet. These are shown in Table 5.4. In this table, n signifies the number of components that you are going to use in your filter; k signifies the position of the element. You can get a diagrammatic view of the system by referring to Figure 5.19. The values in the tables are constants but they represent Henries or Farads according to Table 5.4 Butterworth normalised values k/n 2 3 4 5 6 7 8 1 1.4142 1.0000 0.7654 0.6180 0.5176 0.4550 0.3902 2 1.4142 2.0000 1.8478 1.6180 1.4142 1.2470 1.1111 3 1.0000 1.8478 2.0000 1.9319 1.8019 1.6629 4 0.7654 1.6180 1.9319 2.0000 1.9616 5 0.6180 1.4142 1.8019 1.9616 6 0.5176 1.2470 1.6629 7 0.4450 1.1111 8 0.3902 Butterworth filter 211 the configuration in which they are used. This is best demonstrated by using simple 5.4.2 Low pass filter design A typical procedure for low pass filter design is given below, followed by a design example. Procedure to design a low pass filter 1 Decide the passband and stopband frequencies. 2 Decide on the stopband attenuation. 3 Decide on the type of filter (Butterworth, etc.) you want to use, bearing in mind that some types such as the Butterworth filter give better amplitude characteristics while the Bessel filter gives better group delay. 4 Calculate the number of arms you need to achieve your requirements. 5 Calculate or use normalised tables to find the values of the filter elements. These normalised values (in farads and henries) are the component values required to make a low pass filter with an impedance of 1 W and a passband limit frequency ( fp) of one 6 To make a filter having a different impedance, e.g. 50 W, the impedance of each compo- nent must be increased by the impedance ratio, i.e. all inductances must be multiplied and all capacitances must be divided by the impedance ratio. 7 To make a filter having a higher band limit than the normalised 1 rad/s, divide the value of each component by (2p times the frequency). Example 5.4 A five element maximally flat (Butterworth) low pass filter is to be designed for use in a 50 W circuit. Its 3 dB point is 500 MHz. Calculate its component values. Given: Five element low pass Butterworth filter, fp = 500 MHz, Z0 = 50 Ω. Required: Calculation of five elements for a low pass filter. Solution. The required low pass filter circuit is shown in Figure 5.20. The normalised values for this filter will be taken from column 5 of Table 5.4 because we want a five element Butterworth filter. Fig. 5.20 Low pass configuration 212 Amplifier basics Table 5.5 shows how the filter design is carried out. Table 5.5 Calculated values for a low pass Butterworth filter Circuit reference Normalised Z0 = 50 W Z0 = 50 W Z0 = 1 W f = 1/(2p) Hz fp = 500 MHz w = 1 rad/s 0.6180 0.6180 g1 or C1 0.6180 F ——— F ———————— F or 3.93 pF 50 50 × 2p × 500 MHz 1.6180 × 50 g2 or L2 1.6180 H 1.6180 × 50 H —————— H or 25.75 nH 2p × 500 MHz 2.0000 2.0000 g3 or C3 2.0000 F ——— F ———————— F or 12.73 pF 50 50 × 2p × 500 MHz 1.6180 × 50 g4 or L4 1.6180 H 1.6180 × 50 H —————— H or 25.75 nH 2p × 500 MHz 0.6180 0.6180 g5 or C5 0.6180 F ——— F ———————— F or 3.93 pF 50 50 × 2p × 500 MHz Hence, the calculated values for a five element low pass Butterworth filter with a nomi- nal impedance of 50 W and a 3 dB cut-off frequency at 500 MHz are: C1 = 3.93 pF, L2 = 25.75 nH, C3 = 12.73 pF, L4 = 25.75 nH and C5 = 3.93 pF The response of the filter designed in the above example is shown in Figure 5.21. Fig. 5.21 Results of Example 5.4 Alternatively to save yourself work, you can use PUFF for the result. This is shown in Figure 5.22. Butterworth filter 213 Fig. 5.22 Results of low pass filter using PUFF 5.4.3 Low pass filter example Low pass filters can also be designed using transmission lines. We will not do it here because (i) the circuit elements must first be translated into electrical line lengths, and their end capacitances and discontinuities must be calculated, (ii) the effect on the other components must be compensated which means altering line lengths again, and (iii) changing line lengths of each element in turn, then again compensating for the effect of each line length on the other elements. The whole process is rather laborious and is best done by computer design. You can find more detail in filter design from two well known books, the first by Matthei, Young and Jones and the other by T. C. Edwards.2 5.4.4 Low pass filter using microstrip lines We use PUFF to show an example of a distributed low pass filter. Example 5.5 Figure 5.23 shows how a low pass filter can be produced using transmission lines of varying impedances and lengths. You should note that distributed line filters of this type also conduct 2 G. L. Matthei, L. Young and E. M. T. Jones, Microwave filters, impedance matching networks and coupling structures, McGraw-Hill, New York NY, 1964 and T. C. Edwards, Foundations for microstrip design, second edition, John Wiley and Sons, 1992. 214 Amplifier basics Fig. 5.23 Low pass filter construction using microstrip d.c. and that if you want to block d.c. then you should use d.c. blocking components such as series capacitors. For details of the filter elements, refer to the F3 box of Figure 5.23. 5.4.5 High pass filter A typical procedure for high pass filter design is given below. It is immediately followed by a design example. Procedure to design a high pass filter 1 Decide the passband and stopband frequencies. 2 Decide on the stopband attenuation. 3 Decide on the type of filter (Butterworth, etc.) you want to use, bearing in mind that some types such as the Butterworth filter give better amplitude characteristics while the Bessel filter gives better group delay. 4 Calculate the number of arms you need to achieve your requirements. 5 Calculate or use normalised tables to find the values of the filter elements. These normalised values (in farads and henries) are the component values required to make a low pass filter with an impedance of 1 W and a passband limit frequency ( fp) of 1 rad/s. 6 To calculate the corresponding high pass filter, we must (a) replace each capacitor by an inductor and each inductor by a capacitor and (b) give each component a normalised value equal to the reciprocal of the normalised component it replaces. Butterworth filter 215 7 To make a filter having a different impedance, e.g. 50 W, the impedance of each compo- nent must be increased by the impedance ratio, i.e. all inductances must be multiplied, all capacitances must be divided by the impedance ratio. 8 To make a filter having a higher band limit than the normalised 1 rad/s, divide the value of each component by (2p times the frequency). Example 5.6 High pass filter design A five element maximally flat (Butterworth) high pass filter is to be designed for use in a 50 W circuit. Its 3 dB point is 500 MHz. Calculate its component values. Hint: note that this is the high pass equivalent of the low pass filter designed previously. Given: Five element high pass Butterworth filter, fp = 500 MHz, Z 0 = 50 W. Required: Calculation of five elements for a high pass filter. Solution. The circuit is shown in Figure 5.24. Fig. 5.24 High pass configuration The normalised values for this filter will be taken from column 5 of Table 5.4 because we want a five element Butterworth filter. Table 5.6a shows how this is carried out. Table 5.6a Calculated values for a high pass Butterworth filter Circuit reference Normalised Z0 = 50 W Z0 = 50 W Z0 = 1 W f = 1/(2p) Hz fp = 500 MHz w = 1 rad/s 1 50 50 × 109 g1 or L1 ——— H ——— H —————————— = 25.75 nH 0.6180 0.6180 0.6180 × 2p × 500 × 106 1 1 1 × 1012 g2 or C2 ——— F ————— F ———————————— = 3.93 pF 1.6180 1.6180 × 50 1.618 × 50 × 2p × 500 × 106 1 50 50 × 109 g3 or L3 ——— H ——— H —————————— 7.95 nH 2.0000 2.0000 2.000 × 2p × 500 × 106 1 1 1 × 1012 g4 or C4 ——— F ————— F ———————————— = 3.93 pF 1.6180 1.6180 × 50 1.618 × 50 × 2p × 500 × 106 1 50 50 × 109 g5 or L5 ——— H ——— H —————————— = 25.75 nH 0.6180 0.6180 0.6180 × 2p × 500 × 106 216 Amplifier basics Hence, the calculated values for a five element high pass Butterworth filter with a nomi- nal impedance of 50 W and a 3 dB cut-off frequency at 500 MHz are: L 1 = 25.75 nH, C 2 = 3.93 pF, L 3 = 7.95 nH, C4 = 3.93 pF and L 5 = 25.75 nH The response of the filter designed in the above example is shown in Figure 5.25. Fig. 5.25 High pass filter You can verify this design for yourself by using PUFF. Details of this are given in Figure 5.26. Fig. 5.26 High pass filter using PUFF Butterworth filter 217 5.4.6 High pass filter using microstrip lines An example of high pass filter design using microstrip lines is given below. Example 5.7 The construction of a high pass filter using microstrip lines is shown in Figure 5.27. Details of this filter can be found in the same figure. Fig. 5.27 Construction of a high pass filter using transmission lines 5.4.7 Bandpass filter For a bandpass filter, the performance must be specified in terms of bandwidth (see Figure 5.28). The passband limit ( fp ) becomes the difference between the upper frequency limit ( fb ) and the lower frequency limit ( fa ) of the passband, i.e. fp = fb – fa. Similarly the frequency variable ( f ) becomes the frequency difference between any two points on the response curve at the same level: and the stopband limit ( fs ) becomes the frequency differ- ence between the two frequencies ( fx and fy ) outside of which the required minimum stop- band attenuation (A s ) is to be achieved. The response curve will have geometric symmetry about the centre frequency ( f0), i.e. f0 = fa . fb = fx . fy . This means that the cut-off rate in dB/Hz will be greater on the 218 Amplifier basics Fig. 5.28 Bandpass characteristics low frequency side and usually the number of arms required in the filter will be dependent on the cut-off rate of the high frequency side. The normalised stopband limit is given by Ws = (fs/fp ) = (fy – fx )/( fb – fa ) Procedure to design a bandpass filter To evaluate a bandpass filter having a passband from fa to fb: 1 define the pass bandwidth fp = fb – fa; 2 calculate the geometric centre frequency f0 = fa fb ; 3 evaluate as previously the lowpass filter having its passband limit frequency equal to fp; 4 add in series with each inductance (L) a capacitance of value (1/(wo2L) and in parallel with each capacitance (C) an inductance of value (1/(wo2C), i.e. the added component resonates the original component at the band centre frequency f0. Example 5.8 A five element maximally flat (Butterworth) bandpass filter is to be designed for use in a 50 W circuit. Its upper passband frequency limit ( fb ) is 525 MHz and its lower passband frequency limit is 475 MHz. Calculate its component values. Hint: calculate the low pass filter for the passband design bandwidth, then ‘translate’ the circuit for operation at f0 = fa × fb . Given: Five element bandpass Butterworth filter, fp = 50 MHz, Z 0 = 50 W. Required: Calculation of five elements for a high pass filter. Solution. The passband filter components are shown in Figure 5.29. 1 Define the passband frequency; fp = fb – fa = (525 – 475) MHz = 50 MHz 2 Calculate the geometric mean frequency; f0 = fb × fa = 525 × 475 MHz ≈ 499.4 MHz Butterworth filter 219 Fig. 5.29 Bandpass configuration 3 Evaluate the low pass filter having its passband limit frequency equal to fp. Use column 5 of Table 5.4. Table 5.7 Calculated primary values for a bandpass Butterworth filter Circuit reference Normalised Z0 = 50 W Z0 = 50 W Z0 = 1 W f = 1/(2p) Hz fp = 50 MHz w = 1 rad/s 0.6180 0.6180 g1 or C1 0.6180 F ——— F ———————— F or 39.343 pF 50 50 × 2p × 50 MHz 1.6180 × 50 g2 or L2 1.6180 H 1.6180 × 50 H —————— H or 257.513 nH 2p × 50 MHz 2.0000 2.0000 g3 or C3 2.0000 F ——— F ———————— F or 127.324 pF 50 50 × 2p × 50 MHz 1.6180 × 50 g4 or L4 1.6180 H 1.6180 × 50 H —————— H or 257.513 nH 2p × 50 MHz 0.6180 0.6180 g5 or C5 0.6180 F ——— F ———————— F or 39.343 pF 50 50 × 2p × 50 MHz 4 Add in series with each inductance (L) a capacitance of value (1/wo2L) and in parallel with each capacitance (C) an inductance of value (1/wo2C), i.e. the added component resonates with the original component at the band centre frequency ( f0). In this case, f0 = 525 × 475 MHz ≈ 499.4 MHz. Table 5.7(a) Resonating values of a bandpass Butterworth filter Low pass values Resonating values for fo. C1 39.343 pF L1 2.582 nH L2 257.513 nH C2 0.394 pF C3 127.324 pF L3 0.797 nH L4 257.513 nH C4 0.394 pF C5 39.343 pF L5 2.582 nH The response of the filter designed in the above example is shown in Figure 5.30. 220 Amplifier basics Fig. 5.30 Bandpass filter Alternatively, you can use PUFF to give you the results shown in Figure 5.31. Fig. 5.31 Using PUFF to plot results Butterworth filter 221 5.4.8 Bandpass filter design using microstrip lines Example 5.9 An example of a coupled line passband filter using microstrip is shown in Figure 5.32. A coupled filter provides d.c. isolation between the input and output ports. Fig. 5.32 Bandpass filter using coupled microstrip lines Design modifications PUFF permits modification and on-screen comparison of different designs. For this demonstration, we will use Figure 5.32 as a template and produce Figure 5.33. This is carried out by using Figure 5.32, going into the F3 box to change values and then re-plot- ting by pressing the F2 key followed by pressing ctrl + p. Bandpass filter modification Figure 5.33 shows clearly how comparisons can be made to a design prior to final choice and fabrication. 222 Amplifier basics Fig. 5.33 Showing how modifications to a design can be compared to an original design to see if a change is desir- 5.4.9 Bandstop filter For a bandstop filter, the performance must be specified in terms of bandwidth (see Figure 5.34). The stopband limit ( fp ) becomes the difference between the upper frequency limit ( fb ) and the lower frequency limit (fa ) of the passband, i.e. fp = fb – fa. Similarly the frequency variable (f ) becomes the frequency difference between any two points on the response curve at the same level: the stopband limit (fs ) becomes the frequency difference Fig. 5.34 Stoppass characteristics Butterworth filter 223 between the two frequencies (fx and fy ) inside of which the required minimum stopband attenuation (As ) is to be achieved. The response curve will have geometric symmetry about the centre frequency ( f0 ), i.e. f0 = fa fb = fx fy . This means that the cut-off rate in dB/Hz will be greater on the low frequency side and usually the number of arms required in the filter will be dependent on the cut-off rate of the high frequency side. The normalised stopband limit is given by Ws = (fs/fp ) = ( fy – fx)/( fb – fa ) Procedure to design a bandstop filter To evaluate a bandstop filter having a stopband from fa to fb: 1 define the stop bandwidth fp = fb – fa; 2 calculate the geometric centre frequency f0 = fa fb . 3 evaluate as previously the high pass filter having its stopband limit frequency equal to 4 add in series with each inductance (L) a capacitance of value (1/wo2L) and in parallel with each capacitance (C) an inductance of value (1/wo2C), i.e. the added component resonates the original at the band centre f0. Example 5.10 A five element maximally flat (Butterworth) bandstop filter is to be designed for use in a 50 W circuit. Its upper stopband frequency limit ( fb) is 525 MHz and its lower stopband frequency limit is 475 MHz. Calculate its component values. Hint: calculate the high pass filter for the stopband design bandwidth, then ‘translate’ the circuit for operation at f0 = f b f a . Given: Five element band-stop Butterworth filter, fp = 50 MHz, Z 0 = 50 W. Required: Calculation of ten elements for a bandstop filter. Solution. The bandstop filter components are shown in Figure 5.35. Fig. 5.35 Bandstop configuration 1 Define the stopband frequency: fp = fb – fa = (525 – 475) MHz = 50 MHz 2 Calculate the geometric mean frequency f0 = fb × fa = 525 × 475 MHz ≈ 499.4 Mhz 224 Amplifier basics 3 Evaluate the high pass filter having its passband limit frequency equal to fp. The normalised values have originally been taken from column 5 of Table 5.4 but because we are evaluating a high pass filter, the reciprocal values have been used. Table 5.8 Calculated primary values for a bandstop Butterworth filter Circuit reference Normalised Z0 = 50 W Z0 = 50 W Z0 = 1 W f = 1/(2p) Hz fp = 50 MHz w = 1 rad/s 1 50 50 × 109 g1 or L1 ——— H ——— H ————————— = 257.5 nH— 0.6180 0.6180 0.6180 × 2p × 50 × 106 1 1 1 × 1012 g2 or C2 ——— F ————— F ——————————— = 39.3 pF 1.6180 1.6180 × 50 1.618 × 50 × 2p × 50 × 106 1 50 50 × 109 g3 or L3 ——— H ——— H ————————— 79.5 nH — 2.0000 2.0000 2.000 × 2p × 50 × 106 1 1 1 × 1012 g4 or C4 ——— F ————— F ——————————— = 39.3 pF 1.6180 1.6180 × 50 1.618 × 50 × 2p × 50 × 106 1 50 50 × 109 g5 or L5 ——— H ——— H ————————— = 257.5 nH— 0.6180 0.6180 0.6180 × 2p × 50 × 106 4 Add in series with each inductance (L) a capacitance of value 1/(wo2L) and in parallel with each capacitance (C) an inductance of value 1/(wo2C), i.e. the added component resonates with the original components at the band centre f0. In this case, f0 = 525 × 475 MHz ≈ 499.4 MHz. Table 5.9 Resonating values for a bandstop Butterworth filter High pass values Resonating values for f0 L1 257.53 nH C1 0.39 pF C2 39.35 pF L2 2.58 nH L3 79.58 nH C3 1.27 pF C4 39.35 pF L4 2.58 nH L5 257.53 nH C5 0.39 pF The response of the filter designed in the above example is shown in Figure 5.36. Alternatively, you can use PUFF to plot the result as shown in Figure 5.37. Fig. 5.36 Bandstop filter Tchebyscheff filter 225 Fig. 5.37 Bandstop filter using PUFF 5.5 Tchebyscheff filter Figure 5.38 shows the response of a filter with a Tchebyscheff or equal ripple type of char- acteristic. Its response differs from the Butterworth filter in that (i) there is a ripple in the passband response and (ii) the transition region from passband to stopband is more pronounced. In short, the filter ‘trades off’ passband ripple (Am) to achieve a greater skirt loss for the same number of filter components. The penalty for using a Tchebyscheff filter is that there is also greater group-delay distortion. The passband approaches the ideal filter at a number of frequencies, between which the insertion loss is allowed to reach the design limit (Ap). This results in a better approximation and the transition becomes steeper than that of a Butterworth filter with the same number of arms, e.g. for a filter with 0.1 dB passband ripple and having 3, 5 or 7 arms, the 1 dB frequency is 0.86, 0.945 or 0.97 respectively times the 3 dB frequency and the corresponding 40 dB frequency is 3.8, 2.0 or 1.5 times the 3 dB frequency. For As > 20 dB and RLR > 10 dB the number of arms required may be estimated from Figure 5.39. Note that Tchebyscheff type filters, having an even number of arms, may have differ- ent terminal impedances, the ratio of which is a function of Ap, as shown in Figure 5.39. These filters are sometimes designated by ‘b’. Tchebyscheff filters, having an even number of arms and equal terminating impedances, may be designated by ‘c’. 226 Amplifier basics Fig. 5.38 Tchebyscheff filter response Fig. 5.39 Estimate of number of arms for Tchebyscheff filter Tchebyscheff filter 227 The ‘b’ sub-type filters have a slightly greater cut-off rate than the corresponding ‘c’ sub- 5.5.1 Normalised Tchebyscheff tables Normalised tables for the Tchebyscheff filter may be calculated from Equations 5.17 to 5.23. These are: [ ] b = ln coth ——— (5.17) where Am = maximum amplitude of passband ripple in dB g = sinh [ ]—— where n = total number of arms in the filter [ ] (2k – 1)p ak = sin — — — — — , k = 1, 2, . . ., n (5.19) bk = g 2 + sin2 [ ] —— , k = 1, 2, . . ., n g = 1 for n odd, g = tanh2 (b/4) for n even (5.21) g1 = 2a1/g (5.22) 4(ak–1)(ak ) gk = ————— , k = 2, 3, . . ., n (5.23) As you can see the calculations for normalised Tchebyscheff filters are quite formidable. To save you time, we provide Tables 5.10–5.12. Table 5.10 Tchebyscheff normalised values (Am = 0.01 dB) k\n 2 3 4 5 6 7 8 1 0.4488 0.6291 0.7128 0.7563 0.7813 0.7969 0.8072 2 0.4077 0.9702 1.2003 1.3049 1.3600 1.3924 1.4130 3 0.6291 1.3212 1.5773 1.6896 1.7481 1.7824 4 0.6476 1.3049 1.5350 1.6331 1.6833 5 0.7563 1.4970 1.7481 1.8529 6 0.7098 1.3924 1.6193 7 0.7969 1.5554 8 0.7333 228 Amplifier basics Table 5.11 Tchebyscheff normalised values (Am = 0.1 dB) k\n 2 3 4 5 6 7 8 1 0.8430 1.0315 1.1088 1.1468 1.1681 1.1811 1.1897 2 0.6220 1.1474 1.3061 1.3712 1.4039 1.4228 1.4346 3 1.0315 1.7703 1.9750 2.0562 2.0966 2.1199 4 0.8180 1.3712 1.5170 1.5733 1.6010 5 1.1468 1.9029 2.0966 2.1699 6 0.8613 1.4228 1.5640 7 1.1811 1.9444 8 0.8778 Table 5.12 Tchebyscheff normalised values (Am = 0.25 dB)3 k\n 2 3 4 5 6 7 8 1 1.113 1.303 1.378 1.382 1.437 1.447 1.454 2 0.688 1.146 1.269 1.326 1.341 1.356 1.365 3 1.303 2.056 2.209 2.316 2.348 2.367 4 0.851 1.326 1.462 1.469 1.489 5 1.382 2.178 2.348 2.411 6 0.885 1.356 1.462 7 1.447 2.210 8 0.898 5.5.2 Design procedure for Tchebyscheff filters 1 Decide on the number of arms you require to achieve your passband ripple and desired 2 Obtain the normalised values from the Tchebyscheff tables. 3 Follow the same procedures as for the Butterworth design examples for low pass, high- pass, bandpass and stopband filters. Example 5.11 A Tchebyscheff 50 W low pass filter is to be designed with its 3 dB cut-off frequency at 50 MHz. The passband ripple is not to exceed 0.1 dB. The filter must offer a minimum of 30 dB attenuation at 100 MHz. Find (a) the number of arms. Given: 50 W low pass Tchebyscheff filter, passband ripple ≤ 0.1 dB, minimum attenua- tion at 100 MHz ≥ 30 dB. Required: (a) Number of arms of low pass filter, (b) component values for filter. (a) Since 100 MHz/50 MHz = 2 and its reciprocal is 0.5 and assuming a return loss of 20 dB and a passband attenuation of 30 dB from Figure 5.39, it is seen that about five arms will be required. (b) Therefore the filter follows the configuration shown below in Figure 5.40a. The perti- nent values are taken from Table 5.11 and the method of calculation is similar to that of Example 5.4. 3 Further tables may be obtained from Reference Data for Radio Engineers, International Telephone and Telegraph Corporation, 320 Park Avenue, New York 22. Tchebyscheff filter 229 Fig. 5.40a Low pass configuration Table 5.13 Calculating values for a low pass Tchebyscheff filter Circuit reference Normalised Z0 = 50 W Z0 = 50 W Z0 = 1 W f = 1/(2p) Hz fp = 50 MHz w = 1 rad/s 1.1468 1.1468 g1 or C1 0.1468 F ——— F ———————— F or 73.01 pF 50 50 × 2p × 50 MHz 1.3712 × 50 g2 or L2 1.3712 H 1.3712 × 50 H —————— H or 218.23 nH 2p × 50 MHz 1.9760 1.9760 g3 or C3 1.9760 F ——— F ———————— F or 125.73 pF 50 50 × 2p × 50 MHz 1.3712 × 50 g4 or L4 1.3712 H 1.3712 × 50 H —————— H or 218.23 nH 2p × 50 MHz 1.1468 1.1468 g5 or C5 1.1468 F ——— F ———————— F or 73.01 pF 50 50 × 2p × 50 MHz Hence the calculated values for a five element low pass Tchebyscheff filter (Am ≤ 0.1 dB) with a nominal impedance of 50 W and a 3 dB cut-off frequency at 50 MHz are: C1 = 73.01 pF, L2 = 218.23 nH, C3 = 125.73 pF, L4 = 218.23 nH, C5 = 73.01 pF The response of this filter is shown in Figure 5.40b. It has been obtained by using PUFF. Notice that there is a ripple in the passband but, because of the scale we have used, it is not clear. However, you can try this on PUFF and set a small attenuation scale and see the ripple. Alternatively, you can sweep the frequency and notice the variation in S21 in PUFF. 230 Amplifier basics Fig. 5.40b Tchebyscheff low pass filter Example 5.12 A Tchebyscheff 75 W high pass filter is to be designed with its 3 dB cut-off frequency at 500 MHz. The passband ripple is not to exceed 0.25 dB. The filter must offer a minimum of 30 dB passband attenuation at 250 MHz. Find (a) the number of arms required, and (b) the component values. Given: 75 W high pass Tchebyscheff filter, passband ripple ≤ 0.25 dB, minimum attenu- ation at 250 MHz ≥ 30 dB. Required: (a) Number of arms of high pass filter, (b) component values for filter. (a) Since 500 MHz/250 MHz = 2 and its reciprocal is 0.5 and assuming a return loss of 20 dB and a passband attenuation of 30 dB from Figure 5.39, it is seen that about five arms will be required. (b) Therefore the filter follows the configuration shown in Figure 5.41. Fig. 5.41 High pass configuration Summary on filters 231 The pertinent values are taken from Table 5.12 and the method of calculation is similar to that of Example 5.4. Table 5.14 shows how this is carried out. Table 5.14 Calculated values for a low pass Tchebyscheff filter Circuit reference Normalised Z0 = 75 W Z0 = 75 W Z0 = 1 W f = 1/(2p) Hz fp = 500 MHz w = 1 rad/s 1 75 75 × 109 g1 or L1 ——— H ——— H —————————— = 17.27 nH 1.382 1.382 1.382 × 2p × 500 × 106 1 1 1 × 1012 g2 or C2 ——— F ————— F ———————————— = 3.20 pF 1.326 1.326 × 75 1.326 × 75 × 2p × 500 × 106 1 75 75 × 109 g3 or L3 —— —H ——— H —————————— = 10.80 nH 2.209 2.209 2.209 × 2p × 500 × 106 1 1 1 × 1012 g4 or C4 — — —F ————— F ———————————— = 3.20 pF 1.326 1.326 × 75 1.326 × 75 × 2p × 500 × 106 1 75 75 × 109 g5 or L5 — — —H ———H —————————— = 17.27 nH 1.382 1.382 1.382 × 2p × 500 × 106 Hence the calculated values for a five element high pass Tchebyscheff filter (Am ≤ 0.25 dB) with a nominal impedance of 75 W and a 3 dB cut-off frequency at 500 MHz L1 = 17.27 nH, C2 = 3.20 pF, L 3 = 10.80 nH, C4 = 3.20 pF, and L5 = 17.27 nH The response of this filter is shown in Figure 5.42. It has been plotted by using PUFF. Notice the ripple in the passband. 232 Amplifier basics Fig. 5.42 Response of high pass filter using PUFF 5.6 Summary on filters In the previous sections, we have shown you how to synthesise or design low pass, high pass, bandpass and stopband filters using normalised tables for the Butterworth and Tchebyscheff type filters. We have assumed that the unloaded Q of the elements are rela- tively high when compared with the loaded Q of the filter. The calculations for these design examples have been carried out using a spreadsheet. There are computer programs available which will compute filter components and in some cases even produce the microwave circuit layout. Space limitations prevent us from showing you the synthesis of many other filter types. However, the design procedures are similar. Many filter designers have produced normalised tables for various types of filters. If you wish to pursue this topic further, the classical microwave filter design book is by Matthei, Young and Jones.4 Last but not least, you should realise that many programs (e.g. SPICE, AppCAD, PUFF) exist to help you with the calculation and response of these filters. 4 G. Matthei, L. Young and E. Jones, Design of microwave filters, impedance matching networks and coupling structures, McGraw-Hill, New York NY, 1964. Impedance matching 233 5.7 Impedance matching Impedance matching is a vitally important part of amplifier design. There are four main reasons for impedance matching: • to match an impedance to the conjugate impedance of a source or load for maximum power transfer; • to match an amplifier to a certain load value to provide a required transistor gain; • to match an amplifier to a load that does not cause transistor instability; • to provide a load for an oscillator that will cause instability and hence oscillations. 5.7.1 Matching methods There are many means of impedance matching in h.f. and r.f. design. These include: • quarter-wave transmission line matching • capacitive matching • single stub matching • L network matching • double stub matching • pi network matching • transformer matching • T network matching • auto-transformer matching You have already been shown the first three methods. We will now show you the rest. 5.7.2 Transformer matching The schematic of a typical i.f. (intermediate frequency) transformer is shown in Figure 5.43. The primary coil (terminals 1 and 2) consists of a number (N1) turns of wire wound in close magnetic proximity to a secondary winding (terminals 3 and 4) with a number (N2) turns of wire. Both primary and secondary windings are normally wound on to a coil former consisting of magnetic material (iron, ferrite or special magnetic compounds). Voltage V1 is the voltage applied to the primary and V2 is the voltage induced in the secondary by magnetic action. The currents i1 and i2 represent the currents flowing in the primary and secondary windings respectively. Fig. 5.43 Schematic of a typical i.f. transformer Magnetic flux linkage between primary and secondary is nearly perfect and for practi- cal purposes the coupling coefficient between primary and secondary coils is unity.5 5 A transformer is said to have a coupling coefficient of 1 if all the flux produced by one winding links with the other windings. 234 Amplifier basics Manufacturers tend to quote coupling coefficients greater than 0.95 for transformers used in 465 kHz i.f. amplifiers. Unless stated otherwise, from now on it will be assumed that the coupling coefficient is unity. Operating principles The operating principles of these transformers can be easily understood by using Michael Faraday’s law, which states that the voltage (V) induced in a conductor is directly propor- tional to the rate of change of the effective magnetic flux (∂ø/∂t) across it. If we define N as the number of turns of the conductor, and ø as the magnetic field, the induced voltage (V) can be calculated by the following expressions: V1 = N1 —— (5.24) V2 = N2 — (5.25) To calculate the voltage ratio of the transformer we simply divide Equation 5.25 by Equation 5.24 giving V2 N2 — =— — (5.26) V1 N1 V1 N1 — =— — (5.27) V2 N2 Current ratio If we define N as the number of turns, i as the current flowing in a circuit and k as a constant of that circuit, then according to Biot Savart’s law the magnetic field (ø) produced can be written as: ø1 = kN1i1 (5.28) ø2 = kN2i 2 (5.29) Since the magnetic field is the same for both windings in our transformer, we can combine Equations 5.28 and 5.29 to give N1i1 = N2i 2 and by transposing we get i2 N1 —= —— (5.30) i1 N2 If we define Z1 = V1/i1 and Z 2 = V2/i 2, we can obtain the input impedance of a trans- former by dividing Equation 5.26 by Equation 5.30 to give Impedance matching 235 V2/V1 N2/N1 ——— = ——— i2/i1 N1/N2 Transposing the above and substituting for Z1 = V1/i1 and Z 2 = V2 /i2 yields [ ] Z 2 = Z1 —— (5.31) Similarly, by transposing Z1 = Z 2 — (5.32) Equations 5.26, 5.30, 5.31 and 5.32 are suitable for use with ‘ideal’ transformers.6 Example 5.12 The primary winding of a two winding transformer is wound with 16 turns while its secondary has 8 turns. The terminating resistance on the secondary is 16 W. What is its effective resistance at the primary? Assume that the transformer is ‘ideal’ and that the coef- ficient of coupling between the primary and the secondary is 1. Solution. Since the transformer is ‘ideal’ with a coupling coefficient of unity, the answer can be found by applying Equation 5.32 and remembering that Z p = Z 1 and Z s = Z 2. This gives [ ] [ ] N1 16 Zp = Zs —— = 16 × —— = 64 W N2 8 Finally before leaving the subject of transformers for now, I would like to mention the 5.7.3 Auto-transformers The auto-transformer is a transformer in which the secondary winding is tapped off the primary winding. It has the advantage that less copper wire is required for the windings but suffers from the fact that the primary and secondary windings are not directly isolated. Apart from constructional details, Equations 5.24–5.32 apply when the auto-transformer is ideal. The application of transformer action in r.f. design is given in Section 5.7.4. Fig. 5.44 Auto-transformer 6 An ideal transformer is a transformer which has negligible losses and is one in which all powers coupled between windings is purely due to the magnetic field. 236 Amplifier basics 5.7.4 Intermediate frequency (i.f.) amplifier with transformers A schematic of a typical intermediate frequency (i.f.) amplifier is shown in Figure 5.45. This amplifier is designed to operate efficiently at one frequency. The operational frequency of the amplifier is determined by the tuned circuit components, C T and L T. CT represents the total capacitance of the tuned circuit. It includes circuit tuning capacitor, effective output capacitance of the transistor and all stray capacitances. L T represents the effective inductance of the circuit. It is mainly due to the primary winding inductance of T 2. The tapping point on the primary winding is at r.f. earth potential because this point is effectively short-circuited to earth through the power supply decoupling capacitors. The position of the tapping point is very important because it determines the working Q and bandwidth of the amplifier circuit. This will be explained shortly. Intermediate frequency amplifiers are used very extensively in superhet receivers and, to keep costs minimal, standardised construction methods are used in the design of their tuned circuits. Figure 5.46 shows a sectional view of a typical 465 kHz i.f. tuned trans- former. Tuned transformers are available in two main base sizes, 7 × 7 mm and 10 × 10 mm. The tuning capacitor (180 pF for the 7 mm size and 150 pF for the 10 mm size) is mounted within the plastic base of the transformer. The primary tuning coil consists of approximately 200 turns of 0.065 mm diameter wire wound on a ferrite bobbin mounted Fig. 5.45 Schematic diagram of a typical 465 kHz i.f. amplifier Fig. 5.46 Sectioned view of a typical 465 kHz i.f. transformer Impedance matching 237 on a plastic base. This bobbin is shaped like a dumbbell. Unloaded primary coil Qs tend to be standardised at 70, 100 or 130. The secondary winding consists of about five to eight turns of wire. Magnetic flux linkage between primary and secondary is nearly perfect and for practical purposes the coupling coefficient between primary and secondary coils is unity.7 Manufacturers tend to quote coupling coefficients greater than 0.95. Unless stated otherwise, from now on it will be assumed that the coupling coeffi- cient is unity. All coil leads are welded to pins on the base. Welding is used to ensure that coil connec- tions do not become detached during external soldering operations. Circuit resonance is adjusted by varying tuning inductance. This is done by altering the position of the ferrite cap relative to the winding bobbin. The tuned circuit load impedance presented by transformer T2 to its driving transistor is set by using the primary winding of T2 as an auto-transformer and by careful choice of winding ratios between n1, n2 and n3. See Figures 5.45 and 5.47. Three resistances are reflected into the primary of T2. These are shown in Figure 5.47. Fig. 5.47 Equivalent tuned circuit of Figure 5.45 The impedance (R ′L) reflected into the primary circuit of T1 by R L in the secondary is given by [ ] n1 + n2 R′L = ———— × RL (5.33) Rcircuit represents the resistive losses associated with the use of non-perfect capacitors, inductors and transformers. It is Rcircuit = Qunloaded woLT or Qunloaded/woCT (5.34) R tr represents the output resistance of the transistor transformed across the tuned circuit, Rtr = [(n1 + n2)/n 2]2 × Rtransistor (5.35) These three resistances in parallel form Reqv . Therefore Reqv = R′ L //Rcircuit //R′tr (5.36) The collector load of the transistor is the ratio {n2/(n1 + n 2 )}2 × R′ L //Rcircuit across the total primary winding. Therefore 7 A transformer is said to have a coupling coefficient of 1 if all the flux produced by one winding links with the other windings. 238 Amplifier basics [ ] Transistor load = ——— × RL //Rcircuit (5.37) n1 + n2 Example 5.14 In Figure 5.47, n 1 = 160, n 2 = 40, n3 = 8 and RL = 2 kW. The resistive losses associated with the tuning capacitor and inductors can be assumed to be negligible and the transistor output resistance reflected across the primary of the tuned circuit is so large that it can be neglected. The magnetic coupling coefficients between coils may be assumed to be unity. (a) What is the transistor load impedance at resonance? (b) If the tapping point on L T is changed so that n 1 = 150 and n 2 = 50, what is the new transistor load impedance at resonance? (a) At resonance, the tuned circuit impedance is very high when compared to the reflected load R′L from the secondary. Using Equation 5.33 n 1+ n 2 2 160 + 40 2 R′L = ——— n3 ] [ — × R L = ———— × 2000 = 1 250 000 W 8 ] Using Equation 5.37 and noting in this case that Reqv = R′L, the transistor load impedance [ ] [ ] n2 40 ——— × R′L = ———— × 1 250 000 = 50 kW n1 + n 2 160 + 40 (b) When n1 = 150 and n2 = 50, using Equation 5.33 [ ] [ ] n1 + n2 150 + 50 R′L = ——— — × R L = ———— × 2000 = 1 250 000 W n3 8 Using Equation 5.33 and noting in this case that R eqv = R′L, the transistor load impedance [ ] [ ] n2 50 ——— × R′L = ———— × 1 250 000 = 78.5 kW n1 + n2 150 + 50 Example 5.14 shows clearly that different collector load impedances can be obtained from a standard tuned i.f. transformer simply by altering the tapping point on the primary coil. For clarity in understanding the previous example, it was assumed that tuned circuits losses (Rcircuit) were negligible and that the reflected output resistance of the transistor (R′tr) was so high that it did not affect the value of R eqv. In practice, the additional resistive losses across the tuned circuit are not negligible and must be taken into account in designing the amplifier. The effect of these additional losses is demonstrated in Example 5.14. Example 5.15 In Figure 5.45, n1 = 160, n2 = 40, n3 = 8 and R L = 2 kW. The unloaded Q of the tuned circuit is 100. The value of the tuning capacitor is 180 pF and the circuit is resonant at 465 Impedance matching 239 kHz. If the coupling coefficient between coils is unity, what is the transistor load imped- ance at resonance? Assume the output impedance of the transistor to be 100 kW. Solution. At resonance, the effective tuned circuit impedance is the parallel value of the reflected load (R′L) from the secondary, the equivalent loss resistance of the tuned circuit (Rcircuit) and the reflected output resistance of the transistor (Rtr). Using Equation 5.33, the reflected load [ ] [ ] n1 + n2 160 + 40 R′L = ——— × R L = ———— × 2000 = 1.25 MW n3 8 The effective loss resistance of the tuned circuit is obtained by using Equation 5.34: R circuit = Q/(woCT) = 100 /(2p × 465 × 103 × 180 × 10–12) = 190.143 kW Using Equation 5.35 [ ] [ ] n1 + n2 160 + 40 2 R tr = ——— × R transistor = ———— × 100 000 = 2.5 MW n2 40 Using Equation 5.37, the transistor load impedance is [ ] [ ] n2 40 ——— × R′L//R circuit = ———— × 154.8 kW ≈ 6.19 kW n1 + n2 160 + 40 The answer to Example 5.15 clearly indicates that the unloaded Q of the tuned circuit affects the transistor collector load and that the transformation ratio must be changed if the original load impedance of 50 kW is desired. Another interesting point is that the loaded Q of the circuit has also fallen drastically because the effective resistance (R eqv) across the tuned circuit has been reduced. Example 5.16 The unloaded Q of a tuned circuit is 100. The value of its tuning inductance is 650 mH and the circuit is resonant at 465 kHz. When the circuit is loaded by the input resistance of a transistor, the effective resistance across the ends of the tuned circuit is 125 kW. What is its loaded Q and 3 dB bandwidth? Solution. Using Equation 5.10 R eqv = Qloaded woL R eqv 125 000 Q loaded = ——— = ——————————— = 65.8 ωoL 2π × 465 000 × 650 × 10–6 From Equation 5.11 Qloaded = ————— 240 Amplifier basics f0 465 000 bandwidth = ——— = ———— = 7066 Hz Qloaded 65.8 Examples 5.15 and 5.16 have brought out a very important point. It is that transistor collector load impedance and circuit bandwidth can be altered independently (within limits) by careful choice of the ratios between n1, n 2, and n 3. This independence of the two is possible even when standard i.f. transformers are used. 5.7.5 Capacitive matching For tuned circuits at the higher frequencies, smaller inductance values are required. Smaller inductance values mean fewer turns and trying to make impedance transformers with the correct transformation ratio is difficult. In cases like that, it is often more conve- nient to use capacitors as the matching element. One such arrangement is shown in Figure Fig. 5.48 Capacitive divider method Capacitive divider matching Capacitive divider matching (Figure 5.48) is particularly useful at very high frequencies (VHF) where the number of turns on an inductor is small and where location of a connec- tion to produce an auto-transformer from the inductor is not practical. The capacitive matching network of Figure 5.48 can be easily obtained by defining Z1 = V1/I1 and Z2 = V2/I2 For ease of analysis, we shall assume that XL (Xc1 + Xc2), and that Z 2 is not loading the circuit. Then by inspection V1 V2 I1 = ———— and I2 = —— Xc1 + Xc2 Xc2 I2 V2 Xc1 + Xc2 —— = —— × ———— I1 Xc2 V1 Impedance matching 241 and transposing V1 V2 Xc1 + Xc2 —— = —— × ———— I1 I2 Xc2 and substituting for Z 1, Z 2 and reactances [ ] 1/jwC1 + 1/jwC 2 Z1 = Z 2 ——————— 1/jwC 2 and multiplying all terms by jwC1C 2 [ ] C1 + C 2 Z1 = Z 2 ———— (5.38) Example 5.17 In the circuit shown in Figure 5.48, C1 = 10 pF, C 2 = 100 pF and Z 1 = 22 kW. If the reac- tance of the inductor is very much greater than the combined series reactance of C1 and C 2, calculate the transformed value shown as Z 2. Solution. Using equation 5.38: [ ] [ ] C1 10 Z 2 = Z 1 ———— = 22 000 ———— = 2 kW C1 + C 2 10 + 100 5.7.6 Impedance matching using circuit configurations Many circuit configurations can be used as matching networks. In Figures 5.49, 5.50 and 5.51 we show three circuits which are often used for impedance matching. In Figure 5.49, Z1 and Z 2 are used to match the load Z L to the source Z s. In Figure 5.50, Z a and part of Z b are used for matching to Z1, while the remaining half of Z b and Z c are used for matching to Z 2. In Figure 5.51, Z a and part of Z b are used for matching to Z1 while the remaining part of Z b and Z c are used to match to Z 2. Fig. 5.49 Matching L network 242 Amplifier basics Fig. 5.50 Matching π network Fig. 5.51 Matching T network The details of how these circuits can be used to provide matching will be explained shortly but for ease of understanding, we shall first review some fundamental concepts on the series, parallel and Q equivalents of components. 5.7.7 Series and parallel equivalents and quality factor of components Before we can commence network matching methods, it is best to revise some fundamen- tal concepts on the representation of capacitors and inductors. Series and parallel forms and Qs of capacitors Capacitors are not perfect because their conducting plates contain resistance and their dielectric materials are not perfect insulators. The combined losses can be taken into account by an equivalent series resistance (R s ) in the series case or by an equivalent paral- lel resistance (R p) in the parallel case as shown in Figure 5.52. In this diagram, R s and Cs represent the series equivalent circuit of the capacitor while R p and Cp represent the paral- lel equivalent circuit. The parallel representation is preferred when dealing with circuits where elements are connected in parallel. Quality factor (Q) of a capacitor. We will follow normal convention and define the series quality factor (Qs ) as reactance 1/wCs 1 Qs = ————— = ——— = ——— (5.39) resistance Rs wCsR s w = angular frequency in radians Cs = capacitance in Farads R s = equivalent series resistance (ESR) of a capacitor in ohms Impedance matching 243 Fig. 5.52 Series and parallel form of a ‘practical’ capacitor Similarly, we will define the parallel quality factor (Qp) as susceptance ωCp Qp = —————— = —— = ωCpR p — (5.40) conductance 1/R p ω = angular frequency in radians Cp = capacitance in Farads R p = equivalent parallel resistance (EPR) of a capacitor in ohms Example 5.18 A capacitor has an equivalent parallel resistance of 15 000 W and a capacity of 100 pF. Calculate its quality factor (Qp) at 100 MHz. Solution. Using Equation 5.40: Qp = wCpR p = 2p × 100 MHz × 100 pF × 15 000 = 942.48 ≈ 943 Equivalence of the series and parallel representations. The purpose of this section is to show the relationships between series and parallel circuit representations. Using the same symbols as before and referring to Figure 5.52 { } 1 1 R s – 1/ jwCs Y = ——————— = ————— × ————— impedance (Z) R s + 1/jwCs R s – 1/jwCs Rs 1/jwCs G + jB = ————— – —————— R 2 + ——— s R 2 + ——— w 2C 2 s w 2C 2 Using Equation 5.39: R s/R 2 s Qs /R s G + jB = ———— + j ———— 1 + Q2 s 1 + Q2 s 244 Amplifier basics 1 Qs /R s G + jB = ————— + j ———— (5.41) R s(1 + Q 2) s 1 + Q2 s Equating ‘real’ parts of Equation 5.41: G = —— = ————— Rp R s(1 + Q 2) R p = R s(1 + Q 2 ) s (5.42) Qs = —— – 1 (5.43) Equation 5.43 is used extensively in the matching of L networks which will be discussed If Q > 10, then from Equation 5.42 R p ≈ R sQ 2 s (5.44) Equating imaginary parts of Equation 5.41 Qs /Rs B = ωCp = ——— 1 + Q2 s and using Equation 5.42 gives wCp = ———————— ———— (1 + Q 2) (1 + Q 2) Transposing R p and using Equation 5.40 for Qp wCpR p = Qp = Qs (5.45) Substituting Equation 5.39 for Qs in Equation 5.45 and transposing w and R p 1 Cs Cp = ————— × —— w 2Cs Rs Rp Cs and substituting Equation 5.42 for R p Q 2Cs Cp = ———— (5.46) (1 + Q 2) Impedance matching 245 If Qs > 10, then from Equation 5.46 Cp ≈ —— Cs ≈ Cs (5.47) Series and parallel forms and Qs of inductors Quality factor (Qs) of an inductor. The ‘goodness’ or quality factor (Qs ) of an inductor is defined as: Qs = —— (5.48) w = angular frequency in radians Ls = inductance in Henries R s = series resistance of inductor in ohms Example 5.19 An inductor has a series resistance of 8 W and an inductance of 365 mH. Calculate its qual- ity factor (Q) at 800 kHz. Solution. Using Equation 5.48 wLs 2p × 800 × 103 × 365 × 10–6 Qs = —— = ———————————— ≈ 229 Rs 8 Equivalence of the series and parallel representations of inductors. Sometimes, it is more convenient to represent the quality factor (Qp) of an inductor in its parallel form as shown in Figure 5.53. In this diagram, Rs and L s represent the series equivalent circuit, while Rp and L p represent the parallel equivalent circuit. The equivalent values can be calculated by taking the admittance form of the series circuit: { } 1 1 Rs – jwLs Y = —————— = ———— × ————— impedance (Z) Rs + jwLs Rs – jwL s Fig. 5.53 Series and parallel form of an inductor 246 Amplifier basics Rs jwLs G – jBL = ———— – ———— — R 2 + w 2L 2 R 2 + w 2L 2 s s s s Using Equation 5.48 Rs/R 2 s Qs/Rs G – jBL = ——— – j ——— 1 + Q2 s 1 + Q2s 1 1 + Q2 s R p = — = ——— = Rs(1 + Q 2) s (5.49) G 1/Rs Qs = —— – 1 (5.50) Equation 5.50 is used extensively in the matching of L networks which will be discussed If Q > 10, then from Equation 5.49 R p ≈ Rs Q 2 s (5.51) –j –jwLs –jBL = —— = ———— — wL p R 2 + w 2L2 s s Transposing and dividing by w R 2 + w 2L2 s s Lp = ———— — w s 1 + Q2 1 + Q2 = ——— = Qs s { } Ls (5.52) If Qs > 10, then from Equation 5.52 L p ≈ —— Ls ≈ Ls (5.53) Finally, defining the parallel equivalent quality factor (Qp) = susceptance/conductance and using Equations 5.49 and 5.52, it can be shown that Qp = Qs: Rp Rs (1 + Qs ) Q2 Qp = = = s = Qs ωLp ⎧1 + Q 2 ⎫ ⎪ ⎪ Qs (5.54) ω ⎨ 2 s ⎬ Ls ⎪ Qs ⎪ ⎩ ⎭ Impedance matching 247 Example 5.20 The inductor shown in Figure 5.53 has a series resistance (R s) of 2 W and inductance (Ls) of 15 mH. Calculate its equivalent parallel resistance (R p), parallel inductance (L p) and its equivalent quality factor (Qp), at 10 MHz. Solution. From Equation 5.48 wLs 2p × 10 × 106 × 15 × 10–6 942.5 Qs = —— = ——————————— = ——— ≈ 471 Rs 2 2 From Equation 5.49 R p = R s(1 + Q 2) = 2 × (1 + 4712) ≈ 444 kW From Equation 5.52 1 + Q2 1 + 4712 Lp = { }——— Ls = 15 × 10–6 { } ———— ≈ 15 µH From Equation 5.54 Qp = Qs = 471 Note: Since Qs is very high in this case, the approximate formulae in Equations 5.51 and 5.53 could have been used. 5.7.8 L matching network L matching networks are frequently used to match one impedance to another. They are called L matching networks because the two reactances used (Xa and Xb) are arranged in the form of a letter L. Figure 5.54 shows a common L type network used when it is desired to match the input impedance of a transistor to a network. In this circuit, Cin and R in represent the input impedance of the transistor. C2 is put in parallel with Cin to form a total capacitance Ct; therefore Xb = 1/jwCt. Xa = 1/jwC1. Z s is the input impedance looking into the circuit. It follows that Fig. 5.54 Matching L network 248 Amplifier basics 1 Rin(1/jwCt ) Z s = ——— + —————— jwC1 R in + (1/jwCt ) Multiplying the numerator and denominator of the second term by jwCt and normalising [ ] 1 R in 1 – jwCt R in Z s = —— + ———— × ————— jwC1 1 + jwCt R in 1 – jwCt R in which when multiplied out results in wCt R in2 [ ] R in 1 Z s = —————— – j —— + ————— — (5.55) 1 + (wCt R in)2 wC1 1 + (wCt R in)2 The first term is real and shows that the resistance R in has been transformed. The reactive term is incorporated into the tuning capacitance of the input tuned circuit. In this particu- lar case, Xa and Xb have turned out to be capacitive, but this is not always the case. In some cases you may find that Xa and/or Xb may be inductive. In Figure 5.55, we wish to use an L network to match a load resistance (R L) of 500 W to a generator resistance (R g) of 50 W. 1 We begin by deciding on the type of reactance (inductive or capacitive) we would like to use for X p. 2 We then calculate the equivalent series combination of series resistance (Rs) and series reactance (Xs) from the parallel combination of X p and (R p = R L) . You already know how to do this. See Figure 5.54 and Equations 5.49 to 5.54. However, here we must make the transformed R s = R generator = R g to ensure matching conditions for maximum power transfer from the generator to the transformed load. 3 We evaluate Xa so that it cancels out the transformed reactance (Xs) in the circuit. 4 Then we calculate the value Xb. An example will help to clarify the method. Fig. 5.55 Using a L network for matching Impedance matching 249 Example 5.21 Calculate a matching network for the circuit shown in Figure 5.55. Solution. We begin by choosing X p to be inductive. Next, we use Equation 5.50 which is repeated below for convenience: Qs = Rp Rs − 1 Note in this case that R p is the load resistance (R L) of 500 W and that we want R s = 50 W to match the generator resistance (R g) of 50 W. Substituting these values, we obtain, Qs = 500 50 − 1 = 3 Using Equation 5.48, and again remembering that R g = R s, we have Qs = wLs/Rs and transposing yields R sQ s 50 × 3 L s = —— = —————— = 239 nH w 2p × 100 MHz Xs = wL s = 2p × 100 MHz × 239 nH = 150 W Xa must be chosen to cancel out this inductive reactance of 150 W so X a must be a capac- itor whose reactance X a = 150 W = 1/wCa. Therefore at 100 MHz Ca = 1/(2p × 100 MHz × 150) = 10.6 pF All that remains now is to calculate the parallel value of L p. For this we make use of Equation 5.52, where 1 + Q2 1 + 32 Lp = { ——— } { Ls = ——— } 239 nH = 265 nH The L network is now complete and its values are shown in Figure 5.56. Using PUFF software to check Example 5.21 The results are shown in Figure 5.57. Note that since the matching circuit has been designed to match a 50 W generator, it follows that S11 will be zero when the transformed network matches the 50 W generator at the match frequency. Fig. 5.56 Completed L matching network 250 Amplifier basics Fig. 5.57 PUFF plot of Example 5.21 matching network In the real world, R s and/or R L has associated reactances. Suppose R L is 500 W with a shunt capacitance of 42 pF. How do we solve this problem? This is best explained by using another example. Example 5.22 Calculate a matching network for the circuit shown in Figure 5.58. Solution. This is similar to Example 5.20, except that this time the load resistance (R L) is shunted by a capacitance of 42 pF (see Figure 5.58). The solution proceeds as follows: 1 Introduce an inductance (L) to negate the effect of Cshunt at the frequency of operation, that is, choose L so that XL = XC (see Figure 5.59). Fig. 5.58 L matching network Impedance matching 251 Fig. 5.59 Using an inductor of 60 nH to resonate with the 42 pF 2 Solve for Xa and Xp as in Example 5.21. 3 Solve for the combined value of the two shunt inductors shown in Figure 5.60. Fig. 5.60 The intermediate L network The required value of L is L = ——— — = ————————— = 60.3 nH ≈ 60 nH [2p(100 MHz)]2(42 pF) See Figure 5.59. 4 Calculate the network as in example 5.21. I shall take the values directly from it. See Figure 5.60. 5 Solve for the combined value of the equivalent inductor: Lcombined = ———— ≈ 49 nH 265 + 60 See Figure 5.61 for the final network. Fig. 5.61 Completed L network 252 Amplifier basics In Example 5.22, Xa has been chosen to be capacitive while Xp has been chosen to be inductive. The network could equally have been designed with Xa inductive and Xp capac- itive. In this case, the shunt capacitance of the load should be subtracted from the calcu- lated value of the capacitance forming Xp. For example, if the calculated value of the matching shunt capacitance is 500 pF, then all you need do is subtract the load shunt capacitance (42 pF) from the calculated shunt value (500 pF) and use a value of (500 – 42) pF or 458 pF for the total shunt capacitance and use this value to calculate Xa. Using PUFF software to check Example 5.22 The results are shown in Figure 5.62. Note that since the matching circuit has been designed to match to a 50 W source, it follows that S11 will be zero at the match Fig. 5.62 PUFF plot of Example 5.21 matching network 5.8 Three element matching networks Three or more element matching networks are used when we wish to match and also control the Q of a circuit. If you examine Equation 5.50 which is repeated for convenience, you will see that when R p and Rs are fixed you are forced to accept the value of Q calcu- lated. However, if you can vary either Rp or Rs then you are in a position to set Qs. Using Equation 5.50 again Three element matching networks 253 Qs = —— – 1 (5.50) Varying either R s or R p will no doubt cause a mismatch with your original matching aims. However, you can overcome this by using a second matching L network to match your design back to the source or load. If you examine the p or T network (Figures 5.63 and 5.71) you will see that these networks are made up from two L type networks. Therefore, it is possible to choose (within limits) the Q of the first L network and match it to a virtual value R v then use the second L network to match R v to the load R L. 5.8.1 The p network The p network (Figure 5.63) can be described as two ‘back to back’ L networks (Figure 5.64) that are both configured to match the source and the load to a virtual resistance R v located at the junction between the two networks. More details are provided in Figure 5.65. The significance of the negative signs for –Xs1 and –Xs2 is symbolic. They are used merely to indicate that the Xs values are the opposite type of reactance from Xp1 and Xp2 respectively. Thus, if Xp1 is a capacitor, Xs1 must be an inductor and vice-versa. Similarly if Xp2 is an inductor, Xs2 must be a capacitor, and vice- versa. They do not indicate negative reactances (capacitors). The design of each section of the p network proceeds exactly as was done for the L networks in the previous section. The virtual impedance or resistance Rv in Figure 5.65 must be smaller than either Z1 or Z 2 because it is connected to the series arm of each L section, but otherwise it can be any value of your choice. Most of the time, Rv is deter- mined by the desired loaded Q of the circuit that you specify at the beginning of the design Fig. 5.63 π network Fig. 5.64 π network made up from two L networks 254 Amplifier basics For our purposes, the loaded Q of the network will be defined as: Q = ( Rh Rv ) − 1 (5.56) Rh = the largest terminating value of Z1 or Z 2 Rv = virtual impedance or resistance Although not entirely accurate, it is a widely accepted Q-determining formula for this circuit, and it is certainly close enough for most practical work. Example 5.23 illustrates the procedure. Example 5.23 A source impedance of (100 + j0) W is to be matched to a load impedance of (1000 + j0) Ω. Design four p networks with a minimum Q of 15 to match the source and load impedances. Given: R s = 100 W, R L = 1000 W, Q = 15. Required: To design four types of p matching networks. Solution. Take the output L network on the load side of the p network. From Equation 5.56, we can find the virtual resistance (R v) that we will be matching: Rh 1000 R v = ——— = ——— = 4.425 W Q 2+ 1 152 + 1 To find X p2 we use Equation 5.10: Rp RL 1000 Xp2 = —— = —— = ——— = 66.667 W Qp Qp 15 Similarly to find Xs2, we use Equation 5.4: Xs2 = Q × R series = 15(R v) = (15) (4.425) = 66.375 W This completes the design of the L section on the load side of the network. Note that Rseries in the above equation was substituted for the virtual resistor (R v) which by definition is in the series arms of the L section. The Q for the input (source) L section network is defined by the ratio of Rs to R v, as per Equation 5.56, where: Rs 100 Q1 = −1 = − 1 = 4.647 Rv 4.425 Notice here that the source resistor is now considered to be in the shunt leg of the L network. Therefore R s is defined as R p, and using Equation 5.10 Rp 100 Xp1 = —— = ——— = 21.612 W Q1 4.627 Three element matching networks 255 Fig. 5.65 Practical details of a π network Similarly, using Equation 5.4: Xs1 = Q1R series = (4.647)(4.425) = 20.563 W The actual network is now complete and is shown in Figure 5.65. Remember that the virtual resistor (R) is not really in the circuit and therefore is not shown. Reactances –Xs1 and –Xs2 are now in series and can simply be added together to form a single component. So far in this design, we have dealt only with reactances and have not yet computed actual component values. This is because of the need to maintain a general design approach so that the four final networks requested in the example can be generated Note that Xp1, Xs1, Xp2 and Xs2 can all be either capacitive or inductive reactances. The only constraint is that Xp1 and Xs1 are of opposite types, and Xp2 and Xs2 are of opposite types. This yields the four networks shown in Figures 5.66 to 5.69. Note that both the source and load have been omitted in these figures. Each component in Figures 5.66 to 5.69 is shown as a reactance in ohms. Therefore to perform the transformation from dual L to p network, the two series components are merely added if they are the same type, and subtracted if the reactances are of opposite type. The final step is to change each reac- tance into a component value of capacitance and inductance at the frequency of opera- Fig. 5.66 Matching π network used as a low pass filter Fig. 5.67 Matching π network used as a high pass filter 256 Amplifier basics Fig. 5.68 Matching π network using inductors Fig. 5.69 Matching π network using capacitors Using PUFF software to check Example 5.23 The results are shown in Figure 5.70. For convenience, all four networks have been plot- ted. S11, S22, S33 and S44 are the results of Figures 5.66, 5.67, 5.68 and 5.69 respectively. Note that each of the networks produce the desired input impedance of approximately 100 W.1 You can check this in the Message box of Figure 5.70. Fig. 5.70 PUFF verification of Example 5.23 1 In this particular case, I have carried out the solution at 500 MHz but the components can be selected for oper- ation at other frequencies. Three element matching networks 257 5.8.2 The T network The T network is often used to match two low impedance values when a high Q arrange- ment is needed. The design of the T network is similar to the design for the p network except that with the T network, you match the source and the load with two L type networks to a virtual resistance (R v) which is larger than either of the load or source resis- tance. This means that the two L type networks will then have their shunt arms connected together as in Figure 5.71. Fig. 5.71 T network shown as two back-to-back L networks As mentioned earlier, the T network is often used to match two low-valued impedances when a high Q arrangement is desired. The loaded Q of the T network is determined mainly by the L section that has the highest Q. By definition, the L section with the high- est Q will occur at the end which has the smallest terminating resistor. Each terminating resistor is in the series leg of each network. Therefore the formula for determining the loaded Q of the T network is Q= −1 (5.57) Rv = virtual resistance R small = the smallest terminating resistance The above expression is similar to the Q formula that was previously given for the p network. However, since we have reversed the L sections to produce the T network, we must ensure that we redefine the Q expression to account for the new resistor placement in relation to those L networks. In other words, Equations 5.56 and 5.57 are only special applications for the general formula that is given in Equation 5.50 and repeated here for Qs = −1 (5.58) R p = resistance in the shunt arm of the L network R s = resistance in series arm of the L network Do not be confused with the different definitions of Q because they are all the same in this case. Each L network is calculated in exactly the same manner as was given for the p network previously. We will now show this with Example 5.24. 258 Amplifier basics Example 5.24 Using the configuration shown in Figure 5.71 as a reference, design four different networks to match a 10 W source to a 50 W load. Design each network for a loaded Q of Solution. Using Equation 5.57, we can find the required R v for the match for the required R v = R small(Q 2 + 1) = 10(102 + 1) = 1010 W Using Equation 5.4 Xs1 = QR s = 10(10) = 100 W Using Equation 5.10, Xp2 = R/Q = 1010/10 = 101 W Now for the L network on the load end, the Q is defined by the virtual resistor and the load resistor. Thus Q2 = R RL − 1 = 1010 50 – 1 = 4.382 Ω Xp2 = R/Q 2 = 1010/4.382 = 230.488 W Xs2 = Q sR L = (4.382)(50) = 219.100 W The network is now complete and is shown in Figure 5.72 without the virtual resistor. The two shunt reactances of Figure 5.72 can again be combined to form a single element by simply substituting a value that is equal to the combined parallel reactance of the two. Fig. 5.72 Calculated values for the general T network The four possible T type networks that can be used are shown in Figures 5.73 to 5.76. Fig. 5.73 Low pass T configuration Broadband matching networks 259 Fig. 5.74 High pass T configuration Fig. 5.75 Inductive matched T section Fig. 5.76 Capacitive matched T section Using PUFF software to check Example 5.24 Fig. 5.77 PUFF verification of Example 5.23 260 Amplifier basics Using PUFF software to check Example 5.24 The results are shown in Figure 5.77. For convenience, all four networks have been plot- ted. S11, S22, S33 and S44 are the results of Figures 5.73, 5.74, 5.75 and 5.76 respectively. Note that each of the networks produces the desired input impedance of approximately 10 W. You can read this in the Message box of Figure 5.77. 5.9 Broadband matching networks With regard to the L network, we have noted that the circuit Q is automatically defined when the source and load are selected. With the p and T networks, we can choose a circuit Q provided that the Q chosen is larger than that which is available with the L network. This indicates that the p and T networks are useful for narrow band matching. However, to provide a broadband match, we use two L sections in still another configuration. This is shown in Figures 5.78 and 5.79 where R v is in the shunt arm of one L section and in the series arm of the other L section. We therefore have two series-connected L sections rather than the back-to-back connection of the p and T networks. In this new configuration, the value of R v must be larger than the smallest termination impedance but also smaller than the largest termination impedance. The net result is a range of loaded Q values that is less than the range of Q values obtainable from either a single L section, or the p or T networks previously described. The maximum bandwidth (minimum Q) available from the networks of Figures 5.78 and 5.79 occurs when R v is made equal to the geometric mean of the two impedances being matched: Rv = Rs RL (5.58) The loaded Q of the above networks is defined as: Rv Rlarger Q= −1 = −1 (5.59) Rsmaller Rv Fig. 5.78 Series connected L networks for lower Q applications. Rv is shunt leg Fig. 5.79 Series connected L networks for lower Q applications. R is series leg Summary of matching networks 261 Fig. 5.80 Expanded version of Figure 5.80 for even wider bandwidth Rv = the virtual resistance R smaller = smallest terminating resistance R larger = largest terminating resistance For wider bandwidths, more L networks may be cascaded with virtual resistances between each network as shown in Figure 5.80. Optimum bandwidths in these cases are obtained if the ratios of each of the two succeeding resistances are equal: R v1 R v2 R v3 R larger ——— = —— = —— = ——— (5.60) R smaller R v1 R v2 . . . Rn R smaller = smallest terminating resistance R larger = largest terminating resistance R v1, R v2, . . ., R vn = the virtual resistances The design procedure for these wideband matching networks is much the same as was given for the previous examples. For the configurations of Figures 5.78 and 5.79, use Equation 5.58 to solve for R v to design for an optimally wideband. For the configurations of Figures 5.78 and 5.79, use Equation 5.58 to solve for R v to design for a specific low Q. For the configuration of Figure 5.80, use Equation 5.60 to solve for the different values of R v. In all three cases after you have determined R v, you can proceed as before. 5.10 Summary of matching networks You should now be able to use several types of matching networks. These include trans- former, capacitor-divider, L, π and T networks. Matching is vitally important in amplifier design because without this ability, it is almost impossible to design good amplifiers and High frequency transistor 6.1 Introduction In this part, it is assumed that you are already familiar with transistors and their opera- tion in low frequency circuits. We will introduce basic principles, biasing, and its effects on the a.c. equivalent circuit of transistors, and the understanding of manufacturers’ tran- sistor data in the early parts of the chapter. The latter half of the chapter is devoted to the design of amplifier circuits. 6.1.1 Aims The aims of this part are to review: • basic principles of transistors • biasing of transistors • a.c. equivalent circuit of transistors • manufacturers’ admittance parameters transistor data • manufacturers’ scattering parameters transistor data • manufacturers’ transistor data in graphical form • manufacturers’ transistor data in electronic form 6.1.2 Objectives After reading this part, you should be able to: • understand basic operating principles of transistors • understand manufacturers’ transistor data • apply manufacturers’ transistor data in amplifier design • bias a transistor for proper operation • check for transistor stability • design amplifiers using admittance parameters 6.2 Bi-polar transistors The word transistor is an abbreviation of two words transferring resistor. Bipolar transistors 263 Fig. 6.1(a) Basic construction of an NPN transistor and Fig. 6.1(b) Basic construction of a PNP transistor and its its symbolic representation symbolic representation Fig. 6.2 The Ebers Moll model of a transistor 6.2.1 Basic construction The basic construction of bi-polar transistors and their electrical symbolic representations are shown in Figure 6.1. The arrow indicates the direction of current flow in the transistor. Many transistors are made in complementary pairs. Typical examples are the well known NPN and PNP industrial and military types, 2N2222 and 2N2907, which have been used for over four decades and are still being used in many designs. 6.2.2 Transistor action1 For explanation purposes, a transistor may be considered as two diodes connected back to back. This is the well known Ebers Moll model and it is shown in Figure 6.2 for the NPN transistor. In the Ebers Moll model, a current generator is included to show the relation- ship (Ic = aIe) between the emitter current (Ie) and the collector current (Ic). In a good tran- sistor, a ranges from 0.99 to about 0.999. 1 Although the description is mainly for NPN transistors, the same principles apply for PNP transistors except that, in the latter case, positive charges (holes) are used instead of electrons. 264 High frequency transistor amplifiers Fig. 6.3 Bi-polar transistor action The action that takes place for an NPN transistor can be explained by the diagram in Figure 6.3. In this diagram, emitter, base and collector are diffused together and a base–emitter depletion layer is set up between base and emitter, and a collector–base depletion layer is set up between the collector and base. These depletion layers are set up in the same way as p–n junctions. In normal transistor operation, the base–emitter junction is forward biased and the base–collector junction is reversed biased. This results in a narrow depletion (low resis- tance) at the base–emitter junction and a wide depletion layer (high resistance) at the collector–base junction. Electrons from the emitter (Ie) are attracted to the base by the positive potential Vbe. By the time these electrons arrive in the base region, they will have acquired relatively high mobility and momentum. Some of these electrons will be attracted towards the positive potential of Vbe but most of them (>99%) will keep moving across the base region which is extremely thin (≈0.2 – 15 microns2) and will penetrate the collector–base junction. The electrons (Ic) will be swept into the collector region where they will be attracted by the positive potential of Vcb. Relatively little d.c. energy is required to attract electrons into the base region because it is forward biased (low resistance – Rbe). Relatively larger amounts of d.c. energy will be required in the collector–base region because the junction is reversed biased (high resis- tance – Rcb). 2 1 micron is one millionth of a metre. Bi-polar transistors 265 Nevertheless we have transferred current flowing in a low resistance region into current flowing in a high resistance region. The ratio of the powers dissipated in these two regions power in the collector–base region 2 I c Rcb ——————————————— = ——— power in the base–emitter region 2 I e Rbe Ic = collector current Ie = emitter current Rcb = resistance between collector and base Rbe = resistance between base and emitter Since by design, Ic ≈ Ie and since Rcb >> Rbe I 2Rcb c Rcb ——— ≈ ——— (6.1) I c be Rbe We have a power gain because Rcb >> Rbe. Hence if signal energy is placed between the base–emitter junction, it will appear at a much higher energy level in the collector region and amplification has been achieved. 6.2.3 Collector current characteristics If you were to plot collector current (IC) of an NPN transistor against collector–emitter (VCE) for various values of the base current (IB), you will get the graph shown in Figure 6.4. In practice, the graph is either released by transistor manufacturers or you can obtain it by using an automatic transistor curve plotter. The points to note about these characteristics are: • the ‘knee’ of these curves occurs when VCE is at about 0.3–0.7 V; • collector current (IC) increases with base current (IB) above the ‘knee’ voltage. Fig. 6.4 Collector current characteristics 266 High frequency transistor amplifiers 6.2.4 Current gain Because of the slightly non-linear relation between collector current and base current, there are two ways of specifying the current gain of a transistor in the common emitter circuit. The d.c. current gain (hFE) is simply obtained by dividing the collector current by the base current. This value is important in switching circuits. At point P1 of Figure 6.4, when VCE = 10 V and IB = 40 µA, Ic = 25 mA. Therefore collector current hFE = ——————— = 25 mA/40 mA = 625 (6.2) base current For most amplification purposes, we are only concerned with small variations in collector current, and a more appropriate way of specifying current gain is to divide the change in collector current by the change in base current and obtain the small signal current gain hFE or b. At point P2 of Figure 6.4, when the operating point is chosen to be at around VCE = 5 V, and I = 20 mA DIc (14 – 12) mA hFE = —— = ——————— = 1000 (6.3) DIb (21 – 19) mA 6.2.5 Operating point The point at which a transistor operates is very important. For example at point P2 of Figure 6.4 (see inset), if we choose the operating point to be at VCE = 5 V and IC = 13 mA, it is immediately clear that you will not get VCE excursions è 5 V because the transistor will not function when VCE = 0. The same argument is true with current because you will not get current excursions less than zero. Therefore the operating point must be carefully chosen for your intended purpose. This act of choosing the operating point is called bias- ing. The importance of biasing cannot be over-emphasised because, as you will see later, d.c. biasing also alters the a.c. parameters of a transistor. If the a.c. parameters of your transistor cannot be held constant (within limits) then your r.f. design will not be stable. 6.2.6 Transistor biasing The objectives of transistor biasing are: • to select a suitable operating point for the transistor; • to maintain the chosen operating point with changes in temperature; • to maintain the chosen operating point with changes in transistor current gain with • to maintain the chosen operating point to minimise changes in the a.c. parameters of the operating transistor; • to prevent thermal runaway, where an increase in collector current with temperature causes overheating, burning and self-destruction; • to try to maintain the chosen operating point with changes in supply voltages – this is particularly true of battery operated equipment where the supply voltage changes considerably as the battery discharges; Bi-polar transistors 267 • to maintain the chosen operating point with changes in b when a transistor of one type is replaced by another of the same type – it is common to find that b varies from 50% to 300% of its nominal value for the same type of transistor. There are two basic internal characteristics that have a serious effect upon a transistor’s d.c. operating point over temperature. They are changes in the base–emitter voltage (DVBE) and changes in current gain (Db). As temperature increases, the required base-emitter volt- age (VBE) of a silicon transistor for the same collector current decreases at the rate of about 2.3 mV/°C. This means that if VBE was 0.7 V for a given collector current before a temper- ature rise, then the same VBE of 0.7 V after a temperature rise will now produce an increase in base current and more collector current; that in turn causes a further increment in tran- sistor temperature, more base and collector current, and so on, until the transistor eventu- ally overheats and burns itself out in a process known as thermal runaway. To prevent this cyclic action we must reduce the effective VBE with temperature. Sections 6.2.7 to 6.2.9 indicate several ways of biasing bi-polar transistors in order to increase bias stability. Complete step-by-step design instructions are included with each circuit configuration. For ease of understanding, a.c. components such as tuned circuits, inductors and capacitors have deliberately been left out of the circuits because they play little part in setting the operating bias point. However, a.c. components will be considered at a later stage when we come to design r.f. amplifiers. 6.2.7 Voltage feedback bias circuit One circuit that will compensate for VBE is shown in Figure 6.5. Any increase in the quies- cent3 collector current, (IC) causes a larger voltage drop across RC which reduces VC which in turn reduces IB and IC. This can be shown by: Fig. 6.5 Voltage feedback biasing 3 Quiescent collector current is defined as the collector current which is desired at a given temperature and with no signal input to the transistor. 268 High frequency transistor amplifiers IB = (VC – VBE)/RF (6.4) VC = VCC – (IC + IB)RC (6.5) Substituting Equation 6.4 in Equation 6.5 yields VC = VCC – ICRC – RC(VC – VBE)/RF ICRC = VCC – VC – RCVC/RF + RCVBE /RF and differentiating IC with respect to VBE and cancelling RC from both sides gives ∂IC = ∂VBE/RF (6.6) Equation 6.6 shows clearly that the effect of variations in VBE on IC is reduced by a factor of 1/RF in Figure 6.5. Example 6.1 Given the transistor circuit of Figure 6.5 with hFE = 200 and VCC = 10 V find an operating point of IC = 1 mA and VC = 5 V. Given: Transistor circuit of Figure 6.5 with hFE = 200, VCC = 10 V. Required: An operating point of IC = 1 mA and VC = 5 V. Solution Using Equation 6.2 IB = IC/hFE = 1000/200 = 5 µA Assuming VBE and transposing Equation 6.4 RF = (VC – VBE)/IB = (5 – 0.7) V/ 5 mA = 860 kW Transposing Equation 6.5 RC = (VCC – VC)/(IC + IB) = (10 – 5) V/(1000 + 5) µA = 4.97 kΩ Three points should be noted about the solution in Example 6.1. • The values calculated are theoretical resistor values, so you must use the nearest avail- able commercial values. • Manufacturers often only quote the minimum and maximum values of hFE. In this case, simply take the geometric mean. For example, if hFE(min) = 100 and hFE(max) = 400, the geometric mean = 100 × 400 = 200. • Thermal runaway is prevented when the half-power supply principle is used; that is when Vc = 0.5VCC. This can be shown as follows. At temperature T0 collector power (P) is given by VC IC = [VCC – ICRC]IC = VCCIC – I CRC (6.7) Bi-polar transistors 269 At a higher temperature (T1) new collector power (P + ∆P) is given by (VC – ∆VC)(IC + ∆IC) ≈ VC(IC + ∆IC) because ∆VC << VC P + DP = [VCC – (IC + ∆IC)RC](IC + ∆IC) = VCC(IC + ∆IC) – (IC + ∆IC)2RC (6.7a) Subtracting Equation 6.7 from Equation 6.7a yields ∆P = VCCIC + VCC ∆IC – (IC2 + 2IC∆IC + ∆IC2)RC – VCCIC + IC2RC Simplifying and discarding ∆IC2RC because it is very small, gives ∆P = ∆IC(VCC – 2 ICRC) Since IC = (VCC – VC)/RC ∆P = ∆IC(– VCC + 2VC) For ∆P to equal zero, we get VCC = 2VC or VC = 0.5VCC (6.8) Equation 6.8 is the basis for the half-power supply principle and it should be used when- ever possible to prevent thermal runaway. For reasons which will become clearer when we discuss a.c. feedback, you will some- times find that RF is split into two resistors, RF1 and RF2, with a capacitor CF1 connected between its junction and chassis ground as shown in Figure 6.6. The purpose of CF1 is to prevent any output a.c. or r.f. signal from travelling back to the input circuit. RF1 is used to prevent short-circuiting the collector output signal via CF1 and RF2 is to prevent short- circuiting the base signal through CF1. Finally before leaving the bias circuits of Figures 6.5 and 6.6, the great advantage of the Fig. 6.6 Split feedback bias circuit 270 High frequency transistor amplifiers voltage feedback circuit is that it enables the emitter to be earthed directly. This is very important at microwave frequencies because it helps to prevent unwanted feedback which may affect amplifier stability. Example 6.2 A transistor has hFE = 250 when VC = 12 V and IC = 2 mA. If your power supply (VCC) is 24 V, design a bias circuit like that shown in Figure 6.5 for operating the transistor with VC = 12 V and IC = 2 mA. Solution For this solution use the outlines of Example 6.1. Using Equation 6.2, hFE = collector current/base current and IB = IC/hFE = 2000 µA/250 = 8 µA Transposing Equations 6.4 and 6.5 RF = (VC – VBE)/IB = (12 – 0.7) V/8 µA = 1.41 MW RC = (VCC – VC)/(IC + IB) = (24 – 12) V/(2000 + 8) µA = 5.97 kW 6.2.8 Voltage feedback and constant current bias circuit Another bias circuit frequently used for r.f. amplifiers is shown in Figure 6.7. This circuit is similar to that shown in Figure 6.5 except that the base current is fed from a more stable source. Any increase in collector current (∆IC) results in a decrease in VC, VBB and IB which in turn counteracts any further increase in IC. The design of this circuit is shown in Example 6.3. Fig. 6.7 Voltage feedback and constant current bias circuit Bi-polar transistors 271 Example 6.3 Using the biasing arrangement shown in Figure 6.7, calculate the biasing resistors for a transistor operating with VC = 10 V, IC = 5 mA and a supply voltage VCC = 20 V. The tran- sistor has a d.c. gain of hFE = 150. Given: VCC = 20 V, VC = 10 V, IC = 5 mA and hFE = 150. Required: R1, RB, RC, RF. 1 Assume values for VBB and IBB to supply a constant current IB: VBB = 2 V IBB = 1 mA 2 Knowing IC and hFE, calculate IB: IC 5 mA IB = —— = ——— = 0.0333 mA hFE 150 3 Knowing VBB and IB, and assuming that VBE = 0.7 V, calculate RB: VBB – VBE (2 – 0.7) V RB = ————— = ————— = 39.39 kW IB 0.0333 mA 4 Knowing VBB and IBB, calculate R1: VBB 2V — — R1 = —— = —— = 2 kW IBB 1 mA 5 Knowing VBB, IBB, IB and VC, calculate RF: VC – VBB (10 – 2) V RF = ————— = ————— = 7.74 kW IBB + IB 1.033 mA 6 Knowing VCC, VC, IC, IB and IBB, calculate RC: VCC – VC (20 – 10) V RC = —————— = ————— = 1.66 kW IC + IB + IBB 6.033 mA Example 6.4 Use the bias circuit shown in Figure 6.7 to set the operating point of a transistor at IC = 1 mA, VC = 6 V. The current gain of the transistor ranges from 100 to 250. The circuit supply voltage is 12 V. Note: In my solution I have chosen VBB = 1.5 V and IBB = 0.5 mA; within reason you may choose other values but if you do then your solutions will obviously differ from 272 High frequency transistor amplifiers Using Example 6.3 as a basis for the solution, I have calculated the values of resistors but you must use the closest commercial value in the circuit. 1 The operating point for the transistor is IC = 1 mA, VC = 6 V, VCC = 12 V and hFE = 100 × 250 ≈ 158 2 Assume values for VBB and IBB to supply a constant current, IB: VBB = 1.5 V IBB = 0.5 mA 3 Knowing IC and hFE, calculate IB: IC 1 mA IB = —— = ——— ≈ 6.3 mA hFE 158 4 Knowing VBB and IB, and assuming that VBE = 0.7 V, calculate RB: VBB – VBE (1.5 – 0.7) V RB = ————— = —————— ≈ 126.9 kW IB 6.3 mA 5 Knowing VBB and IBB, calculate R1: VBB 1.5 V R1 = —— = ——— = 3 kW IBB 0.5 mA 6 Knowing VBB, IBB, IB and VC, calculate RF: VC – VBB (6 – 1.5) V RF = ———— = ———————— = 8.88 kW IBB + IB (0.5 mA + 6.3 mA) 7 Knowing VCC, VC, IC, IB and IBB, calculate RC: VCC – VC (12 – 6) V RC = —————— = —————————— = 3.98 kW IC + IB + IBB (1 + 0.0063 + 0.5) mA 6.2.9 Base-voltage potential divider bias circuit Another bias circuit that is commonly used is the base-voltage potential divider bias circuit shown in Figure 6.8. In this circuit, VBB is held approximately constant by the voltage divider network of R1 and R2. VBE is the voltage difference between VBB and VE which is the product of IE and RE. Since IE = IC + IB, any collector current rise ∆IC is followed by a ∆IE rise which increases VE. This increase in VE is a form of negative feedback that tends to reduce bias on the base–emitter junction and, therefore, decrease the collector current. Example 6.5 shows how to design the bias circuit of Figure 6.8. Bi-polar transistors 273 Fig. 6.8 Base-voltage potential divider bias circuit Example 6.5 Using the biasing arrangement shown in Figure 6.8, calculate the biasing resistors for a transistor operating with VC = 10 V, IC = 10 mA and a supply voltage VCC = 20 V. The tran- sistor has a d.c. gain of hFE = 50. Given: VCC = 20 V, VC = 10 V, IC = 10 mA and hFE = 50. Required: R1, R2, RC, RE. 1 Choose VE to be approximately 10% of VCC. Make VE = 10% of 20 V = 2 V 2 Assume IE ≈ IC for high gain transistors. 3 Knowing IE and VE, calculate RE: RE = ——— = 200 W 10 mA 4 Knowing VCC, VC and IC, calculate RC: VCC – VC (20 – 10) V RC = ——— — = ————— = 1000 W — — IC 10 mA 5 Knowing IC and hFE, calculate IB: IC 10 mA IB = —— = ———— = 0.2 mA hFE 50 274 High frequency transistor amplifiers 6 Knowing VE and VBE, calculate VBB: VBB = VE + VBE = 2.0 V + 0.7 V = 2.7 V 7 Choose a value for IBB; a normal rule of thumb is that IBB ≈ 10IB. Hence IBB = 2 mA 8 Knowing IBB and VBB, calculate R2: VBB 2.7 V R2 = —— = ——— = 1350 W IBB 2 mA 9 Knowing VCC, VBB, IBB and IB, calculate R1: VCC – VBB (20 – 2.7) V R1 = ————— = —————— = 7864 W IBB + IB (2 + 0.2) Example 6.6 Use the bias circuit shown in Figure 6.8 to set the operating point of a transistor at IC = 1 mA, VC = 6 V. The current gain of the transistor ranges from 100 to 250. The circuit supply voltage is 12 V. Note: In my solution I have chosen VE = 1.2 V and IBB = 0.5 mA; within reason you may choose other values but if you do then your solutions will obviously differ from Using Example 6.5 as a basis for the solution, I have calculated the values of resistors but you must use the closest commercial value in the circuit. 1 The operating point for the transistor is: IC = 1 mA, VC = 6 V, VCC = 12 V and hFE = 100 × 250 ≈ 158 2 Assume a value for VE that considers bias stability: choosing VE to be approximately 10% of VCC VE = 10% of 12 V = 1.2 V 3 Assume IE ≈ IC for high hFE transistors. 4 Knowing IE and VE, calculate RE: 1.2 V RE = —— = 1200 W 1 mA 5 Knowing VCC, VC and IC, calculate RC: VCC – VC (12 – 6) V RC = ——— = ————— = 6000 W IC 1 mA Bi-polar transistors 275 6 Knowing IC and hFE, calculate IB: IC 1 mA IB = —— = —— = 6.3 mA hFE 158 7 Knowing VE and VBE, calculate VBB: VBB = VE + VBE = 1.2 V + 0.7 V = 1.9 V 8 I have chosen IBB to be: IBB = 0.5 mA 9 Knowing IBB and VBB, calculate R2: VBB 1.9 V R2 = —— = ———— = 3.8 kW IBB 0.5 mA 10 Knowing VCC, VBB, IBB and IB, calculate R1: VCC – VBB (12 – 1.9) V R1 = ————— = ———————— = 19.95 kW IBB + IB (0.5 + 0.0063) mA 6.2.10 Summary on biasing of bi-polar transistors In the voltage feedback circuits of Figures 6.5 and 6.6 and the voltage feedback and constant current circuit of Figure 6.7, increases of collector current with temperature are kept in check by introducing a form of negative feedback to decrease the effective base–emitter voltage (VBE). If we were to use upward pointing arrows to indicate increases and downward pointing arrows to indicate decreases, for the circuit of Figures 6.5 to 6.7, we would have IC ↑ ; VBE ↓ ; IB ↓ ; → IC constant In the base–voltage potential divider circuit of Figure 6.8, the effective base–emitter volt- age (VBE) is reduced by increasing the emitter voltage (VE) against a quasi fixed potential (VBB). It is a better bias circuit than the earlier ones because VE can be made to almost track and compensate for changes in VBE. Using arrows as before, for the circuit of Figure 6.8, we would have IC ↑ ; VE≠ ↑; (VBE = VBB – VE) ↓ ; IB ↓ ; → IC constant The manufacturing tolerance for hFE or b in transistors of the same part number is typi- cally poor. It is not uncommon for a manufacturer to specify a 10:1 range for b on the data sheet (such as 30 to 300). This of course makes it extremely difficult to design a bias network for the device in question when it is used from a production standpoint as well as a temperature standpoint. However, the base-voltage potential divider circuit works remarkably well on both accounts because a high hFE produces a high VE which counteracts the quasi fixed 276 High frequency transistor amplifiers Fig. 6.9 Active bias circuit for an r.f. amplifier potential VBB. This bias circuit is therefore widely used in production circuits. One draw- back of this circuit is that the resistor RE must be bypassed by a capacitor in order not to affect the a.c. operation of the amplifier. At frequencies less than 100 MHz, this is no prob- lem but at microwave frequencies effective bypassing is difficult and you will see that the earlier circuits are often used. In the discussions on biasing, I have only concentrated on direct biasing where resis- tors are used to control IB and VBE. However, there are active-bias-circuits where one or more additional transistors are used to bias the main r.f. amplifier. One well known exam- ple is shown in Figure 6.9. In this circuit r.f. signal is applied through the input tuned transformer (T1) to the base of the r.f. amplifier (tr1). The r.f. output signal is taken from the collector tuned transformer (T2). Capacitors C1 and C2 are bypass capacitors used to allow r.f. signals to reach the emitter of tr1 easily and to keep r.f. signal out of the bias- ing circuit. Biasing is carried out by supplying base current to tr1 via the secondary of T1 from R4 which in turn is fed from the collector current (IC2) of tr2. The base voltage (VB2) of tr2 is fixed by the potential divider consisting of R1 and R2 which sets the base voltage of tr2 approximately 0.7 V below its emitter voltage (VE2). The emitter voltage (VE2) for tr2 is provided by the voltage drop across R3 which in turn is caused by the collector current (IC1) of tr1. If IC1 increases, then VE2 decreases and the effective base–emitter voltage (VB2) of tr2 decreases, IC2 decreases, which in turn reduces IB1. IC1 then decreases to try and main- tain its old value. Again, if we were to use upward pointing arrows to indicate increases and downward pointing arrows to indicate decreases, for the circuit of Figure 6.9, we would have IC1≠ ↑ ; VE2 ↓ ; VBE2 ↓ ; IC2 ↓ ; IB1 ↓ ; IC1 ↓ ; → IC1 constant The biasing of this circuit can be made very stable and I have used this arrangement for r.f. amplifers operating from –15°C to +75°C. Another advantage of this biasing circuit is that although tr1 is an expensive r.f. transistor, tr2 can be a cheap low frequency transistor. The only requirement is that tr1 and tr2 should be made from similar material to enable easier tracking for VBE and ICO. For example if tr1 is a silicon transistor then tr2 should also be a silicon transistor. Review of field effect transistors 277 6.3 Review of field effect transistors There are two main types of field effect transistors; the junction FET or JFET, and the metal oxide silicon FET or MOSFET. MOSFETs are sometimes also referred to as ‘insu- lated gate field effect transistors’, IGFETs. A high electron mobility FET is also known as a HEMFET. In this discussion, we will look briefly at FET structures, their operating modes and methods of biasing to enable us to use FETs efficiently at high frequencies. 6.3.1 A brief review of field effect transistor (JFET or FET) construction An elementary view of field effect transistor construction will aid understanding when we analyse a.c. equivalent circuits and use them in practical amplifier and oscillator circuits. FET (n-channel) The basic construction of an n-channel type field effect transistor is shown in Figure 6.10. The device has three terminals, a source terminal (S), a gate terminal (G), and a drain terminal (D). In an n-channel depletion mode FET, n-type material is used as the conduct- ing channel between source and drain. P type material is placed on either side of the chan- nel. The effective electrical width of the channel is dependent on the voltage potential (VGS) between gate and source. When electrical supplies are connected in the manner shown in Figure 6.11, electrons flow from the source, past the gate, to the drain. If a negative voltage is applied between the gate and source, its negative electric field will try to ‘pinch’ the electron flow and confine it to a smaller cross-section of the n-channel of the FET. This affects the resistance of the n-channel and restricts the current flowing through it. Hence, by varying the gate–source voltage (VGS), it is possible to control current flow. Power gain is obtained because very little energy is required to control the input signal (VGS) while relatively large amounts of power can be obtained from the variations in drain–source current (IDS). The symbols for an n-channel depletion mode FET and its output current characteristics are shown in Figure 6.12. Drain–source current (ID) is maxi- mum when there is zero voltage on VGS and ID decreases as VGS becomes more negative. The pinch-off voltage (VP) is the gate–source voltage required to reduce the effective cross-section of the n-channel to zero. For practical purposes, it is VGS which causes IDS to Fig. 6.10 An n-channel depletion mode field effect transistor 278 High frequency transistor amplifiers Fig. 6.11 n-channel FET Fig. 6.12 Symbols and output current characteristics for an n-channel FET become zero. IDSS is the drain–source current when the gate and source are shorted together (VGS = 0) for your particular VDS. Operating point and biasing of an n-channel FET Selection of the operating point is similar to that explained for the bi-polar transistor, but the biasing method is different. An example of how to bias an n-channel FET is given in Example 6.7. Example 6.7 Biasing an n-channel FET Using the biasing arrangement shown in Figure 6.13, calculate the biasing resistors for an FET operating with VDS = 10 V, IDS = 5 mA and a supply voltage VCC = 24 V. From manu- facturer’s data, for IDS = 5 mA and VDS = 10 V, VGS = –2.3 V. Given: VCC = 24 V, VDS = 10 V, IDS = 5 mA and VGS = 2.3 V. Required: Rs, RD, RG, R. 1 For our particular transistor, the manufacturer’s d.c. curves show that for an operating current of 5 mA with VDS = 10 V, we require a VGS of –2.3 V which means that the gate must be 2.3 V negative with respect to the source. We do not have a negative supply but we can simulate this supply by making the source positive with respect to the gate which Review of field effect transistors 279 Fig. 6.13 n-channel FET biasing in turn means that the gate will be negative with respect to the source. This is carried out by placing a resistor (RS) in series with ID to produce a positive voltage (VS) which is equal to VGS. We now calculate RS. 2 Since IG = 0, |VGS| = |VS|, and knowing ID, calculating RS gives |VS| |VGS| RS = —— = ——— ID ID 2.3 V = ——— = 460 W 5 mA Note particularly that RS provides a form of negative feedback to stabilise changes in FET parameters with temperature. It also stabilises current when FETs of the same type number are changed, because any increase in IDS immediately produces a correspond- ing decrease in VGS. The ratio change in IDS(∆IDS) change in VGS(∆VGS) is known as the transconductance (gm) of the transistor. 3 Since IG = 0, RG can be chosen to be any convenient large value of resistor – approxi- mately 1 MW. This value is useful because it does not appreciably shunt the desirable high input impedance of the transistor. 4 Knowing VCC, VS, VDS and ID, we can now calculate VD and then RD. Since we require VDS = 10 V and VS has already been chosen as 2.3 V VD = VDS + VS = 10 V + 2.3 V = 12.3 V 280 High frequency transistor amplifiers VCC – VD (24 – 12.3) V RD = ————— = —————— = 2340 W ID 5 mA Our bias circuit is now complete.4 The above biasing circuit is easy to design but complications often arise when the manu- facturer does not supply the d.c. curves for a particular transistor5 or when you cannot obtain the characteristic curve from a transistor curve plotter. In this case, refer to the manufacturer’s FET data sheets for values of VP and IDSS. With these two values known, you can use the well known FET expression for calculating VGS. It is [ ] ID = IDSS 1 – —— (6.9) For our particular case, the manufacturer states that VP = –8 V and IDSS = 10 mA. Substituting the values in Equation 6.9 and transposing yields ⎪ ID ⎫⎪ VGS = VP ⎨1 − ⎬ ⎩ IDSS ⎪ ⎧ 5 mA ⎫ = −8 V ⎨1 − ⎬ ⎩ 10 mA ⎭ = −2.34 V We can then proceed as in steps 3 to 5 above. Example 6.8 An n-channel JFET has VP = –6 V and IDSS = 8 mA. The desired operating point is ID = 2 mA and VDS = 12 V. The supply voltage (VCC) is 24 V. Design a bias circuit for this oper- ating point. Solution: This circuit will be designed following the method given in Example 6.7. 1 The operating point for the transistor is ID = 2 mA, VD = 12 V, VCC = 24 V 2 Vp and IDSS from the data sheet are Vp = –6 V IDSS = 8 mA 4 Older readers might well recognise that this method of biasing is similar to that used for thermionic valves. The only difference is that in thermionic valves, VS is such a small fraction of the anode–cathode voltage that it may be neglected. 5 This seems to be the case with many r.f. transistors. Review of field effect transistors 281 3 Knowing ID, IDSS, and Vp, VGS can be calculated from: ⎪ ID ⎫⎪ VGS = VP ⎨1 − ⎬ ⎩ ⎪ IDSS ⎭ ⎧ 2 mA ⎫ = −6 ⎨1 − ⎬ ⎩ 8 mA ⎭ = −3.0 V 4 Since IG = 0, |VGS| = |VS|, and knowing ID, RS can be calculated: |VS| |VGS| 3 V RS = —— = —— = —— = 1500 W ID ID 2 mA 5 Since IG = 0, RG can be chosen to be any large value of resistor – approximately 1 M W. 6 Knowing VCC, VS, VDS and ID, we can now calculate VD and then RD. Since we require VDS = 12 V and VS has already been calculated as 3 V VD = VDS + VS = 12 V + 3 V = 15 V VCC – VD (24 – 15) V RD = ————— = —————— = 4500 W ID 2 mA The bias circuit is now complete. FET (p-channel ) It is also possible to make p-channel type depletion mode FETs by substituting p-type material for n-type and vice-versa in the simplified construction illustrated in Figure 6.10. However, the voltage supplies must also be reversed to that shown in Figure 6.11, and this time the current flow is ‘hole’ current instead of electrons. The net result is the same and gain can be obtained from the FET. Figure 6.14 shows the symbol for a p-channel FET and Fig. 6.14 Symbols and output current characteristics for a p-channel FET 282 High frequency transistor amplifiers its output current characteristics. Note that VDS and ID are reversed to that for the n-chan- nel characteristics given earlier, and that VGS must be positive to decrease ID. Selection of the operating point is similar to that explained for the bi-polar transistor, but the biasing method is different. An example of how to bias a p-channel FET is given in Example 6.9. Example 6.9 Using the biasing arrangement shown in Figure 6.15, calculate the biasing resistors for a FET operating with VDS = –10 V, IDS = –5 mA and a supply voltage VCC = –24 V. From manufacturer’s data, for IDS = 5 mA and VDS = –10 V, VGS = +2.3 V. Given: VCC = –24 V, VDS = –10 V, VGS = +2.3 V, IDS = –5 mA. Required: RG, RD, RS. Fig. 6.15 Bias circuit for a p-channel depletion mode FET 1 For our particular transistor, the manufacturer’s d.c. curves show that for an operating current of –5 mA with VDS = –10 V, we require a VGS of +2.3 V which means that the gate must be 2.3 V positive with respect to the source. We do not have another power supply but we can simulate this supply by making the source negative with respect to the gate which in turn means that the gate will then be positive with respect to the source. This is carried out by placing a resistor (RS) in series with ID to produce a nega- tive voltage (–VS), which is equal to VGS. We now calculate RS. 2 Since IG = 0, |VGS| = |VS|, and knowing ID, calculating RS gives |VS| |VGS| –2.3 V RS = —— = —— = ——— = 460 W ID ID –5 mA 3 Since IG = 0, RG can be chosen to be any convenient large value of resistor – approxi- mately 1 MW. This value is useful because it does not appreciably shunt the desirable high input impedance of the transistor. Review of field effect transistors 283 4 Knowing VCC, VS, VDS and ID, we can now calculate VD and then RD. Since we require VDS = –10 V and VS has already been chosen as –2.3 V –VD = –VDS – VS = –10 V – 2.3 V = –12.3 V VCC – VD (–24 V) – (–12.3 V) RD = ———— = ———————— = 2340 W ID –5 mA Our bias circuit is now complete. The above biasing circuit is easy to design but complications often arise when the manu- facturer does not supply the d.c. curves for a particular transistor and when you cannot obtain the characteristic curve from a transistor curve plotter. In this case, refer to the manufacturer’s FET data sheets for values of VP and IDSS and use Equation 6.9 as before. With these two values known, you can calculate VGS. Example 6.10 A p-channel JFET is to be operated with ID = –2 mA, VDS = –8 V. The power supply volt- age (VCC) is –14 V. The data sheet gives VP = 4 V and IDSS = –6 mA. Solution: The bias circuit will be designed using Example 6.9 as a guide. 1 The operating point for the transistor is ID = –2 mA, VDS = –8 V, VCC = –14 V 2 For our particular transistor, VP = 5 V and IDSS = –6 mA. 3 Knowing ID, IDSS and VP, we can calculate VGS: ⎪ ID ⎫⎪ VGS = VP ⎨1 − ⎬ ⎩ IDSS ⎪ ⎧ −2 mA ⎫ = 5 ⎨1 − ⎬ ⎩ −6 mA ⎭ = 2.1 V 4 Since IG = 0, |VGS| = |VS|, and knowing ID, calculating RS gives |VS| |VGS| –2.1 V RS = —— = —— = ——— = 1050 W ID ID –2 mA 5 Since IG = 0, RG can be chosen to be any large value of resistor – approximately 1 M Ω. 6 Knowing VCC, VS, VDS and ID, we can now calculate VD and then RD. Since we require VDS = –8 V and VS has already been chosen as –2.1 V: –VD = –VDS – VS = –8 V – 2.1 V = –10.1 V 284 High frequency transistor amplifiers VCC – VD (–14 + 10.1) V RD = ————— = ——————— = 1950 W ID –2 mA Our bias circuit is now complete. 6.3.2 A brief review of metal oxide silicon field effect transistors MOSFETs (n-channel enhancement-mode type) In MOSFETs, the drain and source are p–n junctions formed side by side in the surface of a silicon substrate as illustrated in Figure 6.16. This time the gate is a conductor, originally a metal film (hence the name of the device) but nowadays it is usually a layer of well doped silicon. This gate is separated from the silicon substrate by a film of oxide thus forming an input capacitance. The application of a voltage between gate and source induces carriers in the silicon under the gate – as indicated in Figure 6.17 – the amount of charge induced in the chan- nel being dependent on the gate voltage. When a drain–source voltage is applied (VDS), Fig. 6.16 Basic construction of an n-channel MOSFET Channel of Edge of transition electrons region Fig. 6.17 Basic action in an n-channel MOSFET Review of field effect transistors 285 Fig. 6.18 Symbols and characteristic curves for an n-channel enhancement-mode MOSFET these induced carriers flow between source and drain – the larger the induced charge, the greater the drain current ID. In short, VGS controls the current flowing through the channel for a fixed value of VDS. Power gain is obtained because very little energy is required to control the input signal (VGS) while relative large amounts of power can be obtained from the variation in drain–source current (IDS). The symbols for an n-channel enhancement-mode MOSFET and its output current characteristics are shown in Figure 6.18. Note that in the first symbol, the substrate is marked ‘B’ for bulk to distinguish it from the ‘S’ for source. Sometimes the substrate is joined to the source internally to give a device with three rather than four terminals. The line connecting source and drain is shown as a dashed line to indi- cate that in an n-channel enhancement-mode MOSFET, the conduction channel is not established with zero gate–source voltage. MOSFETs (p-channel enhancement-mode type) It is also possible to make p-channel enhancement-mode MOSFETs by substituting p-type material for n-type and vice-versa to that shown in Figure 6.16. However, the voltage supplies must also be reversed to that shown in Figure 6.17, and this time the current flow is hole current instead of electrons. The net result is the same and gain can be obtained from the MOSFET. Figure 6.19 shows the symbol for a p-channel MOSFET and its output current characteristics. Note that VDS and ID are reversed to that for the n-channel charac- teristics given above. Fig. 6.19 Symbols and characteristic curves for a p-channel enhancement-mode MOSFET 286 High frequency transistor amplifiers Here again, in the first symbol, the substrate is marked ‘B’ for bulk to distinguish it from the ‘S’ for source. However, the arrow is pointing away this time to indicate a p-chan- nel device. Sometimes the substrate is joined to the source internally to give a device with three rather than four terminals. The line connecting source and drain is shown as a dashed line to indicate that in a p-channel enhancement-mode MOSFET, the conduction channel is not established with zero gate–source voltage. Biasing of MOSFETs Selection of the operating point is similar to that explained for the bi-polar transistor. The biasing methods are also similar (see section 6.3.1) but the calculations are simpler because IG = 0. One method of biasing is shown in Example 6.11. Example 6.11 The n-channel enhancement-mode MOSFET shown in Figure 6.20 is to be operated with ID = 5 mA, VDS = 10 V with a supply voltage (VCC) of 18 V. Manufacturer’s data sheets show that this MOSFET requires a positive bias of 3.2 V for a current of 5 mA when VDS is 10 V. Calculate the values of resistors required for the circuit in Figure 6.20. 1 The operating point for the transistor is ID = 5 mA, VDS = 10 V, VCC = 18 V 2 From the manufacturer’s data sheet VGS = +3.2 V for a current of 5 mA. 3 Choose VS to be approximately 10% of VCC: VS = 10% of 18 V = 1.8 V 4 Knowing VS and ID, calculate RS: VS 1.8 V RS = — = —— = 360 W ID 5 mA Fig. 6.20 Bias circuit for an n-channel enhancement-mode MOSFET Review of field effect transistors 287 5 Knowing VS and VGS, calculate VG: VG = VGS + VS = (3.2 + 1.8) V = 5.0 V 6 Assume a value for R2 based upon d.c. input resistance needs: R2 = 220 kW 7 Knowing R2, VG and VCC, calculate R1: R2(VCC – VG) R1 = —————— 220 kW (18–5) V = ———————— = 572 kW 8 Knowing VS and VDS, calculate VD and then RD: VD = VS + VDS = 1.8 V + 10 V = 11.8 V VCC – VD (18 – 11.8) V RD = ———— = —————— = 1240 W ID 5 mA The bias circuit is now complete. Example 6.12 An n-channel enhancement-mode MOSFET is to be operated with ID = 2 mA, VDS = 6 V with a supply voltage (VCC) of 12 V. Manufacturer’s data sheets show that this MOSFET requires a positive bias of 1.8 V for a current of 2 mA when VDS is 6 V. Calculate the values of resistors required for the circuit in Figure 6.20. 1 The operating point for the transistor is ID = 2 mA, VDS = 6 V, VCC = 12 V 2 From the manufacturer’s data sheet VGS = +1.8 V for a current of 2 mA. 3 Choose VS to be approximately 10% of VCC: VS = 10% of 12 V = 1.2 V 4 Knowing VS and ID, calculate RS: VS 1.2 V RS = —— = ——— = 600 W ID 2 mA 5 Knowing VS and VGS, calculate VG: VG = VGS + VS = (1.8 + 1.2) V = 3.0 V 288 High frequency transistor amplifiers 6 Assume a value for R2 based upon d.c. input resistance needs: R2 = 220 kW 7 Knowing R2, VG and VCC, calculate R1: R2(VCC – VG) R1 = ——————— 220 kW (12 – 3) V = ———————— = 660 kW 8 Knowing VS and VDS, calculate VD and then RD: VD = VS + VDS = 1.2 V + 6 V = 7.2 V VCC – VD (12 – 7.2) V RD = ———— = ————— = 2400 W ID 2 mA The bias circuit is now complete. 6.3.3 Depletion-mode MOSFETs Depletion-mode MOSFETs are also known in some books as depletion/enhancement- mode (DE) MOSFETs because, as you will see shortly, they can be biased to operate in both the depletion and enhancement mode. For our purposes, we will refer to them as depletion-mode types to avoid unnecessary confusion. MOSFETs (n-channel depletion-mode type) Depletion-mode MOSFETs are made in a similar way to that of enhancement MOSFETs except that a very thin layer of donors is implanted in the surface of the p-type substrate just under the gate as indicated in Figure 6.21. This is done simply by firing donor atoms Fig. 6.21 A cross-sectional diagram of an n-channel depletion-mode MOSFET showing the layer of donors implanted in the surface of the p-type substrate to form a channel of electrons even when VGS = 0 Review of field effect transistors 289 Fig. 6.22 Symbols and output current characteristics for an n-channel depletion-mode MOSFET in a vacuum at the silicon surface. If the implanted donor density exceeds the density of holes already there, a channel of electrons will be formed even when VGS = 0 and a drain current will flow as soon as VDS is applied. The current which flows in a depletion-mode MOSFET when VGS = 0 is called IDSS and it is quoted in data sheets. Figure 6.22 shows the symbols and electrical characteristics of an n-channel depletion- mode MOSFET. Note that VGS can be positive, zero or negative. The VGS required to reduce ID to zero is called the threshold voltage (VT). In the first symbol of Figure 6.22, the substrate is marked ‘B’ for bulk to distinguish it from the ‘S’ for source. Sometimes the substrate is joined to the source internally to give a device with three rather than four termi- nals. The line connecting source and drain is shown as a full line to indicate that in an n-channel DE-mode MOSFET, a conduction channel is present even with zero gate–source MOSFETs (p-channel depletion-mode type) MOSFETs (p-channel depletion-mode) are made in a similar manner to that shown for the n-channel depletion-mode MOSFET except that p-type material has been substituted for n-type material and operating voltages must be reversed. The symbols and current charac- teristics of a p-channel depletion-mode MOSFET are shown in Figure 6.23. The explanation of the operation of p-channel MOSFETs is identical to that of the n-channel MOSFET just described except that all region types, carrier types, voltages Fig. 6.23 Symbols and output current characteristics for a p-channel depletion-mode MOSFET 290 High frequency transistor amplifiers and currents are reversed. For example the gate is made increasingly negative to cause an increase in drain current, and the threshold voltage of an enhancement-mode p- type channel device is positive. In the first symbol of Figure 6.23, the substrate is marked ‘B’ for bulk to distinguish it from the ‘S’ for source. Sometimes the substrate is joined to the source internally to give a device with three rather than four terminals. The line connecting source and drain is shown as a full line to indicate that in a p-chan- nel DE-mode MOSFET, a conduction channel is present even with zero gate–source Biasing of depletion-mode MOSFETs These MOSFETs can be biased according to the methods given in Examples 6.7, 6.9 and 6.11. The circuit you choose will depend on whether you wish to operate the circuit with positive or negative VGS. 6.3.4 Summary of the properties of FETs and MOSFETs Field effect transistors (FETs) can be regarded as three terminal devices whose terminals are called source, drain and gate. There are two types of field effect transistor; the junction FET or JFET, and the metal oxide silicon FET or MOSFET. In a JFET current flows through a channel of silicon whose cross-sectional area is controlled by a p–n junction whose width is varied by the application of a voltage between gate and source, as illus- trated in Figure 6.11. In a MOSFET the drain and source are p–n junctions formed side by side in the surface of a silicon substrate as illustrated in Figure 6.16. The gate is separated from the silicon substrate by a film of oxide. The application of a voltage between gate and source induces carriers in the silicon under the gate which then forms the channel between source and drain. See Figure 6.17. There are complementary forms of both types of FET: namely n-channel and p-channel devices. In n-channel devices the drain current is carried by electrons, whilst in p-channel devices it is carried by holes. There are two variants of MOSFET called enhancement- mode devices and depletion-mode devices. In enhancement-mode devices ID = 0 when VGS = 0. In depletion-mode devices (and in JFETs) ID = IDSS when VGS = 0. The families of output characteristics of all FETs have the same general form and have been shown in Figures 6.12, 6.14, 6.18, 6.19, 6.22 and 6.23. Note particularly that the polarities of the voltage and directions of currents of p-channel devices are the reverse of those of n-channel ones; and that the differences between the three types of n-channel devices, or between the three p-channel devices, is in their range of values for VGS. The polarity of the threshold voltages (VT) distinguishes between enhancement-mode and depletion-mode MOSFETs. (The threshold voltages are the gate voltages at which the drain current ID just begins to flow.) There are alternative graphical symbols for MOSFETs in common use, which are also shown in Figures 6.12, 6.14, 6.18, 6.19, 6.22 and 6.23. Note that if the (longer) central line represents the piece of silicon, an arrow in a diagram always points at a p-region or away from an n-region, as with bi-polar transistors. However, the arrow indicates the source in a MOSFET, but indicates the gate in a JFET. Note the extra line added to the MOSFET symbols for depletion-mode operation – it is intended to indicate the existence of a chan- nel when VGS = 0. Other symbols may be found in data sheets and in textbooks, so be sure to check the meanings of symbols in other publications. In particular a more complicated A.C. equivalent circuits of transistors 291 standard symbol is used to represent the four terminal nature of MOSFETs, but we shall not be referring to this in this text. The carriers in the channel of either type of FET flow from source to drain under the influence of an electric field, so the currents are drift currents rather than diffusion The d.c. output characteristics of a JFET can be calculated by Equation 6.7. The main electrical advantage of MOSFETs over bi-polar transistors is that their d.c. gate current is virtually zero. This is due to the presence of the oxide layer between the gate electrode and the substrate. The current gain, if it was ever referred to, would be approaching infinity. This means that the input power to the device is very small indeed. The advantage of MOSFETs from a production point of view is that, in general, they are smaller and cheaper to manufacture than bi-polars. Their main disadvantage is that their transconductance6 (gm) is normally much less than that of bi-polars at the same operating current; that is, the control of the output current by the input voltage is normally less effec- tive. It is possible, however, using special construction methods to produce MOSFETs which are capable of operating more efficiently than bi-polars at microwave frequencies. This is particularly true of the high electron mobility field effect transistor known as the HEMFET which will be discussed later in the design of microwave amplifiers. 6.4 A.C. equivalent circuits of transistors Some of the material described in Section 6.4 has already been covered in earlier sections but I need to emphasise some relevant facts to help you understand how a.c. equivalent circuits are derived. In the analyses of a.c. equivalent circuits, apart from a very brief intro- duction to FETs, I will concentrate mainly on the bi-polar transistor because many of the a.c. equivalent circuits (apart from circuit values) apply to JFETs and MOSFETs as well. 6.4.1 A brief review of bi-polar transistor construction The NPN type bi-polar transistor shown in Figure 6.24 is constructed by using a crystalline layer of silicon7 into which carefully controlled amounts of impurities such as arsenic, phosphorus or antimony have been added so that the silicon may be made to provide rela- tively easy movement for electrons. This layer is known as an n-type material because it contains ‘free’ negative electrical charges (electrons). In the NPN transistor, this layer is called the emitter because it has the ability to ‘emit’ electrons under the influence of a voltage potential. A very thin layer of material about 0.2–10 microns8 thick is then laid over the emitter. This layer is called the base layer. It is usually made of silicon with care- fully controlled amounts of impurities such as aluminium, boron, gallium or indium. This 6 Transconductance (gm) is defined as small change in output current (∆IDS) small change in input voltage (∆VGS) 7 Germanium can also be used but its electrical characteristics with temperature are less stable than that of silicon. Therefore, it is becoming obsolete and is only used for special functions or as replacement transistors for older designs. 8 1 micron = 1 × 10–6 metres. 292 High frequency transistor amplifiers Fig. 6.24 Basic construction of a bi-polar transistor layer is known as a p-type layer because there are ‘free’ positive electric charges (holes) in the material. Finally another layer of n-type material is placed over the base layer. This layer is known as the collector because it collects all the current. With suitable operating conditions, and when the transistor is connected to a battery, electrons from the emitter are made to pass through the base which controls current flow to the collector. This type of action occurs in an NPN type transistor. The same type of action described above is possible with a transistor made with PNP type construction, that is with the emitter and collector constructed of p-type material and the base of n-type material. 6.4.2 A brief review of field effect transistor construction The basic construction of an n-channel type field effect transistor is shown in Figure 6.25. In this case, n-type material is used as the conducting channel between source and drain and p-type material is placed on either side of the channel. The effective electrical width of the channel is dependent on the voltage potential between gate and source. When a power supply is connected in the appropriate manner (+ at the drain and – at the source), electrons flow from the source past the gate to the drain. A negative potential applied to the gate alters the channel width of the transistor. This in turn affects the resis- tance of the channel and its current flow. Power gain is obtained because the input power applied to the gate is very much less than the output power. Fig. 6.25 An n-channel depletion-mode field effect transistor 6.4.3 Basic a.c. equivalent circuits As stated earlier and for the sake of clarity, I will concentrate mainly on the bi-polar tran- sistor. However, you should be aware that much of what is said applies to the FET as well A.C. equivalent circuits of transistors 293 Fig. 6.26 Approximate equivalent electrical circuit of a transistor Fig. 6.27 ‘π ’ equivalent circuit of a transistor because its physical construction also produces inter-electrode resistances and capacitances. If you examine Figure 6.24 more closely, you will see that due to the proximity of the emit- ter, base and collector or the source, gate and drain in Figure 6.25, there is bound to be resis- tance and capacitance between the layers. The approximate9 electrical equivalent circuit for Figure 6.24 has been drawn for you in Figure 6.26. The abbreviations used are: Cbe = capacitance between the base and emitter Rbe = resistance between the base and emitter Ccb = capacitance between the collector and base Rcb = resistance between the collector and base Cce = capacitance between the collector and emitter Rce = resistance between the collector and the emitter gmVbe = a current generator which is controlled by the voltage between base and emitter (Vbe) – this generator is present because there is current gain in a transistor gm = a constant of the transistor and its operating point – it is defined as change in collector current (DIc)/change in base–emitter voltage (DVbe) In Figure 6.27, I have simplified the circuit by removing the bulk diagram of the tran- sistor and it now becomes more recognisable as the p equivalent circuit of a transistor. The circuit is called a p equivalent circuit because the components appear in the form of the Greek letter p. The resistances and capacitances in Figure 6.27 are not fixed. They are dependent on the d.c. operating conditions of the transistor.10 For example, if the d.c. current through the transistor increases then Rbe will decrease and vice-versa. Similarly if the voltage across the transistor increases then Cce will decrease and vice-versa.11 These variations are inevitable because d.c. operating voltages and currents affect the physical nature of transistor junctions. 9 The circuit is only approximate because I have not taken into account the resistance and reactances of the lead and its connections. 10 You will no doubt recall from Section 6.2 that the base–emitter junction of a bi-polar transistor is a forward biased p–n junction diode and that the resistance of this junction (Rdiode) varies with current. 11 This is due to the change in the width of the depletion layer described in Section 6.2. 294 High frequency transistor amplifiers Table 6.1 Typical values for a bi-polar transistor Resistance value Capacitance values Reactances at 100 kHz Rbe ≈ 1–3 kW Cbe ≈ 10–30 pF Xbe ≈ 159–53 kW Rbc ≈ 2–5 MW Cbc ≈ 2–5 pF Xbc ≈ 796–318 kW Rce ≈ 20–50 kW Cce ≈ 2–10 pF Xce ≈ 796–159 kW gm 40 mA per volt when the collector current is 1 mA In Table 6.1, I have listed some typical values of components in a p equivalent circuit when a bi-polar transistor is operated as a small signal amplifier with a collector–emitter voltage of 6 V and a current of 1 mA. Much of the discussion that follows is dependent on the relative values of these components to each other. Low frequency equivalent circuit of a transistor If you examine the first and the third columns of Table 6.1, you will see that at 100 kHz • Xbe >> Rbe so that its effect on Rbe is negligible. • Xce >> Rce so that its effect on Rce is negligible. • If you refer to Figure 6.27, you will see that the fraction of the output voltage between the collector and the emitter (Vce) fed back through the feedback path formed by the parallel combination of Rbc and Ccb the parallel combination of Rbe and Cbe is also very small because the parallel combination (Rbc // Xcb) >> (Rbe // Xbe). Therefore it can also be neglected at low frequencies. If you have difficulty understanding this part, refer back to Figure 6.27. The effects of the above mean that the circuit of Figure 6.27 can be re-drawn at low frequencies to be that shown in Figure 6.28. This equivalent circuit is reasonably accurate for frequencies less than 100 kHz. Fig. 6.28 Low frequency equivalent circuit of a transistor High frequency equivalent circuit of a transistor Returning to the p equivalent circuit of Figure 6.27, you will recall that I mentioned earlier that the circuit was only approximate because I did not take lead resistances and reactances into account. When these are added the circuit becomes that shown in Figure 6.29. This circuit is called the hybrid configuration because it is a hybrid of the p circuit. Another resistance (Rbb) known as the base spreading resistance emerges. This is the inevitable resistance that occurs at the junction between the base terminal or contact and the semiconductor material that composes the base. Its value is usually in tens of ohms. Smaller transistors tend to exhibit larger values of Rbb because of the greater difficulty of A.C. equivalent circuits of transistors 295 Fig. 6.29 Hybrid π equivalent circuit connecting leads to smaller surfaces. Inductors Lb, Lc and Le are the inductances of the base, collector and emitter leads respectively. Of the three inductors, Le has the most pronounced effect on circuit performance because of its feedback effect. This is caused by the input current flowing from B via Lb, Rbb, Cbe and Rbe in parallel, and out via Le while the output current opposes the input current since it flows outwards via Lc, the external load, and in again via Le. As frequency increases, the reactance of Le increases and its effect is to produce a larger (Iout × XLe) volt- age to oppose input current flow. Manufacturers tend to minimise this effect by providing two leads for the emitter; one for the input current and the other for the output current. This is the reason why some r.f. transistors have two emitter leads. An increase in operating frequency causes reactances Xbe, Xcb and Xce to decrease and this action will increase their shunting effect on resistances Rbe, Rcb and Rce and eventually the gain of the transistor will begin to fall. The most serious shunting effect is caused by Xcb because it affects the negative feedback path from collector to base and a frequency will be reached when the gain of the transistor is reduced to unity. The unity gain frequency (fT) is also known as the cut-off frequency of the transistor. 6.4.4 Summary From the foregoing discussions, you should have realised that: • transistors come in different shapes and sizes; • they have d.c. parameters as well as a.c. parameters; • a.c. parameters vary with d.c. operating conditions; • a.c. parameters vary with frequency; • a transistor operating under the same d.c. conditions can be represented by different a.c. equivalent circuits at different frequencies; • transistor data given by manufacturers may appear in several ways, namely p, hybrid p, and other yet to be introduced parameters such as admittance (Y) parameters and scat- tering (S) parameters. 6.4.5 The transistor as a two-port network The transistor is obviously a three terminal device consisting of an emitter, base and collector. In most applications, however, one of the terminals is common to both the input 296 High frequency transistor amplifiers Fig. 6.30 (a) Common emitter configuration; (b) common base configuration; (c) common collector configuration and the output network as shown in Figure 6.30. In the common emitter configuration of Figure 6.30(a), the emitter is grounded and is common to both the input and output network. So, rather than describe the device as a three terminal network, it is convenient to describe the transistor as a ‘black box’ by calling it a two port network. One port is described as the input port while the other is described as the output port. These configu- rations are shown in Figure 6.30(a, b, and c). Once the two port realisation is made, the transistor can be completely characterised by observing its behaviour at the two ports. 6.4.6 Two-port networks Manufacturers are also aware that in many cases, knowing the actual value of components in a transistor is of little value to the circuit design engineer because there is little that can be done to alter its internal values after the transistor has been manufactured. Therefore, manufacturers resort to giving transistor electrical parameters in another manner, namely the ‘two port’ approach. This is shown in Figure 6.31. With this approach, manufacturers simply state that for a given transistor operating under certain conditions, what you can expect to find at the input port (port 1) and the output port (port 2), when you apply exter- nal voltages (v1, v2) and currents (i1, i2) to it. Two port parameters come from manufacturers in different representations. Each type of representation can be described with names such as: admittance – Y-parameters transfer – ABCD-parameters hybrid – H-parameters impedance – Z-parameters scattering – S-parameters Smith chart information For radio frequency work, the most favoured parameters are the y-, s- and h-parameters and information on Smith charts which is a convenient graphical display of y- and s- Fig. 6.31 Two port network representation A.C. equivalent circuits of transistors 297 6.4.7 Radio frequency amplifiers Radio frequency (r.f.) amplifiers will be investigated by first considering one method of modelling transistors at radio frequencies. This method will then be used to design an aerial distribution amplifier. R.F. transistor modelling Transistor modelling serves two main purposes. First, it enables a transistor designer to analyse what is happening within a transistor and to design the necessary modifications to improve performance. Second, it enables a circuit designer to understand what is happen- ing within a circuit and to carry out the necessary adjustments to achieve optimum circuit performance from the transistor. The hybrid p model (Figure 6.29) is particularly good for representing the properties of a transistor but as frequencies increase, its shunt reactances cannot be neglected and its equivalent representation becomes increasingly complex. To minimise these complica- tions, electronic circuit designers prefer to treat a transistor as a complete unit or ‘black box’ and to consider its performance characteristics rather than the individual components in its equivalent circuit. One way to do this is to use admittance parameters or y-parameters. In this approach, the transistor is represented as a two-port network with input port (port 1) and output port (port 2) as shown in Figure 6.32(a). In Figure 6.32(a), the details of the compo- nents within the ‘box’ are not given. The equivalent representation shown in Figure 6.32(b) simply tells us that if the input and output voltages v1 and v2 are changing, then the currents i1 and i2 must also be changing in accordance with the equations i1 = y11v1 + y12v2 (6.10) i2 = y21v1 + y22v2 (6.11) i1 is the a.c. current flowing into the input port (port 1) i2 is the a.c. current flowing into the output port (port 2) v1 is the a.c. voltage at the input port v2 is the a.c. voltage at the output port In practice, the values of the y-parameters, y11, y12, y21, y22, are specified at a particu- lar frequency, in a particular configuration (common base, common emitter, or common Fig. 6.32 (a) Admittance parameters; (b) equivalent representation 298 High frequency transistor amplifiers collector) and with stated values of transistor operating voltages and currents. It is impor- tant to remember that y-parameters are measured phasor quantities, obtained by measur- ing external phasor voltages and currents for a particular transistor. From inspection of Equations 6.10 and 6.11, we define ⎧i ⎫ y11 = ⎨ 1 ⎬ (6.12) ⎩ v1 ⎭v2 = 0 ⎧i ⎫ y12 = ⎨ 1 ⎬ (6.13) ⎩ v2 ⎭v1 = 0 ⎧i ⎫ y21 = ⎨ 2 ⎬ (6.14) ⎩ v1 ⎭v2 = 0 ⎧i ⎫ y22 = ⎨ 2 ⎬ (6.15) ⎩ v2 ⎭v1 = 0 Figure 6.33 shows the same transistor (represented by its ‘y’-parameters) being driven by a constant current signal source (is) with a source admittance (Ys). The transistor feeds a load admittance (YL). By inspection of the circuit in Figure 6.33, it can be seen that is = Ysv1 + i1 i1 = is – Ysv1 (6.16) i2 = –YLv2 (6.17) Note the minus sign. This is because current is flowing in the opposite direction to that indicated in the diagram. Circuit parameters can be calculated as follows. Fig. 6.33 Equivalent circuit of a transistor with source (Ys) and load (YL) A.C. equivalent circuits of transistors 299 Voltage gain. Voltage gain (Av) is defined as (v2/v1). Substituting Equation 6.17 in Equation 6.11 i2 = y21v1 + y22v2 = –YLv2 v2(YL + y22) = –y21v1 v2 –y21 — = ———— = Av (6.18) v1 YL + y22 Input admittance (yin). Input admittance (yin) is defined as i1/v1. Substituting Equation 6.18 in Equation 6.10 { } i1 = y11v1 + y12v2 = y11v1 + y12 ———— y22 + YL and transposing i1 y12y21 — = y11 – ——— = Yin (6.19) v1 y22 + yL Current gain (Ai). Current gain (Ai) is defined as i2/i1. From Equations 6.19 and 6.17 i1 –i2 v1 = — and v2 = —— Yin YL and substituting in Equation 6.11 [ ] [ ] i1 i2 i2 = y21 —— – y22 —— Yin YL [ ][ ] YL + Y22 Y21 i2 ———— = —— i1 YL Yin i2 y21YL — = —————— = Ai (6.20) i1 Yin (y22 + YL) Output admittance (Yout). Output admittance (Yout) is defined as [i2/v2] . Substituting is = 0 Equation 6.16 in Equation 6.10 i1 = y11v1 + y12v2 = –Ysv1 (remember is = 0) 300 High frequency transistor amplifiers { } v1 = ———— y11 + Ys Substituting in Equation 6.11 { } i2 = y21 ———— + y22v2 y11 + YS Transposing v2 results in i2 y12y21 — = y22 – ——— = Yout (6.21) v2 y11 + YS Equations 6.18 to 6.21 enable us to calculate the performance of a transistor circuit. The equations are in a general form and apply to a transistor regardless of whether it is operating in the common emitter, common base or common collector mode. The only stipulations are that you recognise that signal enters and leaves the transistor at port 1 and port 2 respectively and that you use the correct set of ‘y’-parameters in the Design case: aerial amplifier design using ‘y’-parameters In this design study (Figure 6.34), the signal is picked up by an aerial whose source imped- ance is 75 W. The signal is then fed into an amplifier whose load is a 300 W distribution system which feeds signals to all the domestic VHF/FM receivers in the house. The design was carried out in the following manner. 1 Manufacturers’ data sheets were used to find a transistor which will operate satisfac- torily at 100 MHz; the approximate centre of the VHF broadcast band. The transistor is assumed to be unconditionally stable. 2 A decision was made on transistor operating conditions. Guidelines are usually given in the data sheets for operating conditions and ‘y’-parameters. Typical operating conditions for a well known transistor with d.c. conditions (Vce = 6 V, Ic = 1 mA) operating in the common emitter mode were found to be: Fig. 6.34 Aerial amplifier design study A.C. equivalent circuits of transistors 301 y11 = (13.752 + j13.946) mS y12 = (–0.146 – j1.148) mS y21 = (1.094 – j17.511) mS y22 = (0.3 + j1.571) mS The relevant information is summarised below. Zs= 75 W or Ys = 13.33 mS ∠ 0° ZL = 300 W or YL = 3.33 mS ∠ 0° y11 = (13.75 + j13.95) mS y12 = (–0.15 – j1.15) mS y21 = (1.09 – j17.51) mS y22 = (0.3 + j1.57) mS Required: (a) Voltage gain (Av), (b) input admittance (Yin), (c) output admittance (Yout). Solution. In this solution, you should concentrate on the method used, rather than the laborious arithmetic which can be easily checked by a calculator. Simpler numerical para- meters were not used because they do not reflect realistic design problems. (a) Use Equation 6.18 to calculate the voltage gain (Av): –y21 1/180° × (1.09–j17.5) mS Av = ———— = —————————————— YL + y22 3.33 mS/0° + (0.3 + j1.57) mS 17.54 mS/93.56° = ———————— = 4.44/70.17° 3.95 mS/23.39° From the above answer, you should note the following. • The phase relationship between the input and output signals is not always the usual 180° phase reversal expected in a low frequency common emitter amplifier. This is because of transistor feedback caused mainly by the reduced reactance of the internal collec- tor–base capacitance at higher radio frequencies. • The gain and phase relationship is also dependent on the magnitude and phase of the load. Figure 6.35 shows the relationships between the input (OA) and output (OB) voltages. It is readily seen that there is a component of the output signal which is in phase with the Fig. 6.35 OA and OB represent input and output phasor voltages 302 High frequency transistor amplifiers input signal. This in-phase component can cause instability problems if it is allowed to stray back into the input port. To keep the two signals apart, good layout, short connecting leads and shielding are essential. If a tuned circuit is used as an amplifier load, its impedance and phase will vary with tuning. This in turn affects the amplitude and phase relationships between amplifier input and output voltages. These variations must be incorporated into the amplifier design other- wise instability will occur. Input admittance (Yin) (b) For this calculation, we use Equation 6.19: Yin = Y11 – ———— Y22 + YL (–0.15 – j1.15) mS (1.09 – j17.51) mS = (13.75 + j13.95) mS – ———————————————— (0.3 + j1.57) mS + 3.33 mS/0° (1.16 mS2 ∠ –97.4°)(17.54 mS ∠ –86.44°) = (13.75 + j13.95) mS – ————————————————— (3.63 + j1.57) mS 20.35 mS ∠ –183.84° = (13.75 + j13.95) mS – —————————— 3.95 mS ∠ 23.39° = (13.75 + j13.95) mS – 5.15 mS ∠ –207.23° = (13.75 + j13.95) mS – (–4.58 + j2.36) mS = (18.33 + j11.59) mS From the answer, you should note Yin is also dependent on the phase of the load admit- tance. This is particularly important in multi-stage amplifiers where the input admittance of the last amplifier provides the load for the amplifier before it. In this case, altering or tuning the load of the last stage amplifier will affect its input admittance and in turn affect the load of the amplifier driving it. This is the reason why the procedure for tuning a multi- stage amplifier usually requires that the last stage be adjusted before the earlier stages. Output admittance (Yout) (c) For this calculation, we use Equation 6.21: Yout = y22 – ———— y11 + Ys (–0.15 – j1.15) mS (1.09 – j17.51) mS = (0.3 + j1.57) mS – ———————————————— (13.75 + j13.95) mS + 13.33 mS ∠ 0°) (1.16 ∠ –97.4°) mS (17.54 ∠ –86.44°) mS = (0.3 + j1.57) mS – ————————————————— — (13.75 + j13.95) mS + 13.33 mS ∠ 0° 20.35 mS2 ∠ –183.84° = (0.3 + j1.57) mS – ————————— (27.08 + j13.95) mS A.C. equivalent circuits of transistors 303 20.35 mS2 ∠ –183.84° = (0.3 + j1.57) mS – ————————— 30.46 mS ∠ 27.25° = (0.3 + j1.57) mS – 0.67 mS ∠ –211.09° = (0.3 + j1.57) mS – (–0.57 + j0.35) mS = (0.87 + j1.22) mS From the answer, you should note Yout is also dependent on the phase of the source admit- tance. This is particularly important in multi-stage amplifiers where the load admittance of the first amplifier provides the source for the amplifier following it. In this case, altering or tuning the load of the first stage will affect the source admittance of the second stage and so on. This is why, having tuned a multi-stage high frequency amplifier once, you usually have to repeat the tuning again to compensate for the changes in the output admit- Theoretically, it would appear that there is no satisfactory way of tuning a multi-stage amplifier because individual amplifiers affect each other. In practice, it is found that after the second tuning, little improvement is obtained if a subsequent re-tune is carried out. Therefore as a compromise between performance and labour costs, most multi-stage amplifiers are considered to be tuned after the second tuning. Summary of the design case. From this design study, you have learnt how to calculate the voltage gain, input and output admittances of a simple amplifier. You should also have under- stood why good shielding and layout practices are important in high frequency amplifiers and the reasons for the procedures used in tuning multi-stage high frequency amplifiers. Example 6.13 Using the parameters given in the case study, calculate the current gain (Ai) of the amplifier. Solution. Using Equation 6.20, current gain (Ai) is defined as i2/i1. Hence i2 y21 YL Ai = — = ————— i1 Yin (y22 + YL) (1.09 – j17.51) mS × 3.33 mS/0° = —————————————————————— (18.33 + j11.59) mS [(0.3 + j1.57) mS + 3.33 mS/0° ] (17.54 ∠ –86.44°) mS × 3.33 × mS/0° = ————————————————— (21.69 ∠ 32.31°) mS (3.96 mS ∠ 23.39°) (58.41 ∠ –86.44°) mS2 = ————————— (85.89 ∠ 55.70°) mS2 = 0.68 ∠ –142.14° Note: Current gain is less than unity. This is because the load admittance is low. 304 High frequency transistor amplifiers 6.5 General r.f. design considerations The example given in the Design Study has been based on a design methodology, where we have assumed that the transistor is unconditionally stable, that gain is not of paramount importance, and that the inherent electrical noise of the amplifier is not prevalent. In real life, ideal conditions do not exist and we must trade off some properties at the expense of others. The designs that follow show you how these trade-offs can be carried out. Design of linear r.f. small signal amplifiers is usually based on requirements for specific power gain at specific frequencies. Other design considerations include stability, band- width, input–output isolation and production reproducibility. After a basic circuit type is selected, the applicable design equations can be solved. Many r.f. amplifier designs fail because the incorrect transistor has been chosen for the required purpose. Two of the most important considerations in choosing a transistor for use in any amplifier design are its stability and its maximum available gain (MAG). Stability, as it is used here, is a measure of the transistor’s tendency to oscillate, that is to provide an output signal with no intended input signal. MAG is a figure-of-merit for a transistor which indicates the maximum theoretical power gain which can be obtained from a transistor when it is conjugately matched12 to its source and load impedances. MAG is never achieved in practice because of resistive losses in a circuit; nevertheless MAG is extremely useful in evaluating the initial capabilities of a transistor. 6.5.1 Stability A major factor in the overall design is the potential stability of the transistor. A transistor is stable if there is no output signal when there is no input signal. There are two main stability factors that concern us in amplifier design, (i) the stability factor of the transistor on its own, and (ii) the stability factor of an amplifier circuit. Linvill stability factor The Linvill stability factor is used to determine the stability of a transistor on its own, that is when its input and output ports are open-circuited. Linvill’s stability factor (C) can be calculated by using the following expression: |yf yr| C = ———————— (6.22) 2gigo – Re (yf yr) |yf yr| = magnitude of the product in brackets yf = forward-transfer admittance yr = reverse-transfer admittance gi = input conductance go = output conductance Re = real part of the product in parentheses 12 A signal source generator (Z ) will deliver maximum power to a load (Z ) when its source impedance (Z g L g = Rg + jXg) = (ZL = RL – jXL). The circuit is said to be conjugately matched because Rg = RL and Xg = –XL. General r.f. design considerations 305 When C < 1, the transistor is unconditionally stable at the bias point and the frequency which you have chosen. This means that you can choose any possible combination of source and load impedance for your device and the amplifier will remain stable providing that no external feedback paths exist between the input and output ports. When C > 1, the transistor is potentially unstable and will oscillate for certain values of source and load impedance. However, a C factor greater than 1 does not indicate that the transistor cannot be used as an amplifier. It merely indicates that you must exercise extreme care in selecting your source and load impedances otherwise oscillations may occur. You should also be aware that a potentially unstable transistor at a particular frequency and/or operating point may not necessarily be unstable at another frequency and/or operating point. If for technical or economical reasons, you must use a transistor with C > 1, then try using the transistor with a different bias point, and/or mismatch the input and output impedances of the transistor to reduce the gain of the stage. The Linvill stability factor (C) is useful in predicting a potential stability problem. It does not indicate the actual impedance values between which the transistor will go un- stable. Obviously, if a transistor is chosen for a particular design problem, and the tran- sistor’s C factor is less than 1 (unconditionally stable), that transistor will be much easier to work with than a transistor which is potentially unstable. Bear in mind also that if C is less than but very close to 1 for any transistor, then any change in operating point due to temperature variations can cause the transistor to become potentially unstable and most likely oscillate at some frequency. This is because Y-parameters are specified at a partic- ular operating point which varies with temperature. The important rule is: make C as small as possible. Example 6.14 When operated at 500 MHz with a Vce of 5 V and Ic = 2 mA, a transistor has the follow- ing parameters: yi = (16 + j11.78) mS yr = (1.55 ∠ 258°) mS yf = (45 ∠ 285°) mS yo = (0.19 + j5.97) mS Calculate its Linvill stability factor. Solution. Using Equation 6.22 |yf yr| C = ——————— 2gigo – Re (yf yr) |(45 mS ∠ 285° × 1.55 mS ∠ 258°| = ————————————————————————— 2 × 16 mS × 0.19 mS – Re (45 mS ∠ 285° × 1.55 mS ∠ 258°) |(69.75 mS2 ∠ 183°| |(69.75 mS2 ∠ 183°| = —————————————— = —————————— 6.08 mS2 – Re (69.75 mS2 ∠ 183°) 6.08 mS2 – (–69.65 mS2) 69.75 mS2 = ——— —— = 0.92 75.73 mS2 306 High frequency transistor amplifiers Since the Linvill stability factor < 1, the transistor is unconditionally stable. However, it is only just unconditionally stable and, in production, changes in transistor parameters might easily cause instability. If due to costs or the desire to stock a minimum inventory of parts, you cannot change the transistor, try another operating bias point. The Stern stability factor (K) The Stern stability factor (K) is used to predict the stability of an amplifier when it is oper- ated with certain values of load and source impedances. The Stern stability factor (K) can be calculated by: 2(gi + Gs) (go + GL) K = ————————— (6.23) |yf yr| + Re (yf yr) Gs = the source conductance GL = the load conductance If K > 1, the circuit is stable for that value of source and load impedance. If K < 1, the circuit is potentially unstable and will most likely oscillate at some frequency or in a production run of the circuit. Example 6.15 A transistor operating at VCE = 5 V, IC = 2 mA at 200 MHz with a source impedance of (50 + j0) W and a load impedance of (1000 + j0) W has the following y-parameters: yi = (4.8 + j4.52) mS yr = (0.90 ∠ 265°) mS yf = (61 ∠ 325°) mS yo = (0.05 + j2.26) mS What is the Stern stability factor of the circuit? YS = 1/(ZS) = 1/(50 + j0) = 20 mS YL = 1/(ZL) = 1/(1000 + j0) = 1 mS Using Equation 6.23: 2(gi + Gs)(go + GL) K = ———————— |yf yr| + Re (yf yr) 2 (4.8 mS + 20 mS) (0.05 mS + 1 mS) = —————————————————————————————— |61 mS ∠ 325° × 0.9 mS ∠ 265°| + Re (61 mS ∠ 325° × 0.9 mS ∠ 265°) 2 (24.8 mS) (1.05 mS) 52.08 mS2 = ————————————— = —————————— 54.9 mS2 + Re (54.9 mS2 ∠ 230°) 54.9 mS2 + (–35.29 mS2) General r.f. design conditions 307 52.08 mS2 = ———— = 2.656 ≈ 2.66 19.61 mS2 Since K > 1, the circuit is stable. Summary of the Linvill and Stern stability factors The Linvill stability factor (C) is useful in finding stable transistors: • if C < 1, the transistor is unconditionally stable; • if C > 1, the transistor is potentially unstable. The Stern stability factor (K) is useful for predicting stability problems with circuits: • if K > 1, the circuit is stable for the chosen source and load impedance; • if K < 1, the circuit is potentially unstable for the chosen source and load. 6.5.2 Maximum available gain The maximum available gain (MAG) of a transistor can be found by using the following MAG = ——— (6.24) MAG is useful in the initial search for a transistor for a particular application. It gives a good indication as to whether a transistor will provide sufficient gain for a task. The maximum available gain for a transistor occurs when yr = 0, and when YL and YS are the complex conjugates of yo and yi respectively. The condition that yr must equal zero for maximum gain to occur is due to the fact that under normal conditions, yr acts as a negative feedback path internal to the transistor. With yr = 0, no feedback is allowed and the gain is at a maximum. In practical situations, it is physically impossible to reduce yr to zero and as a result MAG can never be truly obtained. However, it is possible to very nearly achieve the MAG calculated in Equation 6.24 through a simultaneous conjugate match of the input and output impedances of the transistor. Therefore, Equation 6.24 remains a valuable tool in the search for a transistor provided you understand its limitation. For example, if your amplifier design calls for a minimum gain of 20 dB at 500 MHz, find a transistor that will give you a small margin of extra gain, preferably at least about 3–6 dB greater than 20 dB. In this case, find a transistor that will give a gain of approximately 23–26 dB. This will compensate for realistic values of yr, component losses in the matching networks, and vari- ations in bias operating points. Example 6.16 A transistor has the following Y-parameters: yi = (16 + j11.78) mS yr = (1.55 ∠ 258°) mS yf = (45 ∠ 285°) mS yo = (0.19 + j5.97) mS 308 High frequency transistor amplifiers when it is operated at VCE = 5 V and IC = 2 mA at 500 MHz. Calculate its maximum avail- able gain? Solution. Using Equation 6.24 |yf|2 |45 mS|2 MAG = ——— = ————————— 4gigo 4 × 16 mS × 0.19 mS 2025 mS2 = ———— = 166.53 or 22.21 dB 12.16 mS2 6.5.3 Simultaneous conjugate matching Optimum power gain is obtained from a transistor when yi and yo are conjugately matched to Ys and YL respectively. However the reverse-transfer admittance (yr) associated with each transistor tends to reflect13 any immittance (impedance or admittance) changes made at one port back to the other port, causing a change in that port’s immittance characteris- tics. This makes it difficult to design good matching networks for a transistor while using only its input and output admittances, and totally ignoring the contribution that yr makes to the transistor’s immittance characteristics. Although YL affects the input admittance of the transistor and YS affects its output admittance, it is still possible to provide the transis- tor with a simultaneous conjugate match for maximum power transfer (from source to load) by using the following design equations: [2 gi go − Re( yf yr )]2 − yf yr (6.25) Gs = 2 go when yr = 0 Gs = gi (6.25a) Im (yf yr) Bs = – jbi + ———— (6.26) [2 gi go − Re( yf yr )]2 − yf yr (6.27) GL = 2 gi or by using Equation 6.25 for the numerator GL = ——— (6.27a) 13 If you have forgotten this effect, refer to Equations 6.19 and 6.21. General r.f. design considerations 309 Im(yf yr) BL = – jbo + ———— (6.28 ) 2 gi Gs = source conductance Bs = source susceptance GL = load conductance BL = load susceptance Im = imaginary part of the product in parenthesis The above equations may look formidable but actually they are not because the numera- tors in these sets of equations are similar and need not be calculated twice. A case study of how to apply these equations is shown in Example 6.17. Example 6.17 Design an amplifier which will provide maximum gain for conjugate matching of source and load at 300 MHz. The transistor used has the following parameters at 300 MHz with VCE = 5 V and IC = 2 mA: yi = 17.37 + j11.28 mS yr = 1.17 mS ∠ –91° yo = 0.95 + j3.11 mS yf = 130.50 mS ∠ –69° What are the admittance values which must be provided for the transistor at (a) its input and (b) its output? Given: yi = 17.37 + j11.28 mS yr = 1.17 mS ∠ – 91° yo = 0.95 + j3.11 mS yf = 130.50 mS ∠ – 69° f = 300 MHz, VCE = 5 V and IC = 2 mA Required: (a) Its input and (b) its output admittances for conjugate match. 1 Calculate the Linvill stability factor (C) using Equation 6.22: |yf yr| C = ——————— 2gi go – Re(yf yr) |(130.5 mS ∠ –69°) (1.17 mS ∠ –91°)| = ——————————————————————————— 2 (17.37 mS)(0.95 mS) – Re[(130.5 mS ∠ –69°)(1.17 mS ∠ –91°)] 152.69 mS2 152.69 mS2 = ——————————— = ————— = 0.87 33.00 mS2 – (–143.48 mS2) 176.48 mS2 Since C < 1, the device is unconditionally stable and we may proceed with the design. If C > 1, we would have to be extremely careful in matching the transistor to the source and load as instability could occur. 310 High frequency transistor amplifiers 2 Calculate the maximum available gain (MAG) using Equation 6.24: yf 130.5 mS ∠ − 69° MAG = = 4 gi go 4(17.37 mS)(0.95 mS) 17 030.15 µS2 = = 258 or 24.12 dB 66.01 µS2 The actual gain achieved will be less due to yr and component losses. 3 Determine the conjugate values to match transistor input admittance using Equation [2 gi go − Re( yf yr )]2 − yf yr Gs = 2 go [33 µS2 − Re(152.69 µS2 ∠ − 160°)]2 − 152.69 µS2 1.9 mS [33 µS2 − ( −143.48 µS2 )]2 − 152.69 µS2 1.9 mS [176.48 µS2 )]2 − 152.69 µS2 [13 145.19 − 23 314.24] pS4 = = 1.9 mS 1.9 mS [7830.95] pS4 88.49 µS2 = = = 46.57 mS 1.9 mS 1.9 µS Using Equation 6.26 Im(yf yr) Bs = – jbi + ———— –52.22 mS2 = –j11.28 mS + j ————— = – j38.76 mS 2(0.95 mS) Therefore the source admittance for the transistor is (46.57 – j38.76) mS. The transistor input admittance is (46.57 + j38.76) mS. 4 Determine the conjugate values to match transistor output admittance using Equation Gsgo (46.57)(0.95) mS2 — — GL = —— = ——————— = 2.55 mS gi 17.37 mS Using Equation 6.28 General r.f. design conditions 311 Im(yf yr) BL = – jbo + ———— –52.22 mS2 = – j3.11 mS + j —————— = – j4.61 mS 2 (17.37 mS) Therefore, the load admittance required for the transistor is (2.55 – j4.61) mS. The tran- sistor output admittance is (2.55 + j4.61) mS. 5 Calculate the Stern stability factor (K) using Equation 6.23: 2(gi + Gs)(go + GL) K = ————————— |yf yr| + Re(yf yr) 2(17.37 + 46.57)(0.95 + 2.55) mS2 = ———————————————— |152.69| mS2 + Re(152.69 ∠ –160°) mS2 (2)(63.94)(3.50) mS2 = ——————————— = 48.60 152.69 mS2 + (–143.48) mS2 Since K > 1, the circuit is stable. After you have satisfied yourself with the design, you need to design networks which will give the transistor its required source and load impedances and, within reason, also its operating bandwidth. This can be done by using the filter and matching techniques described in Chapter 5 and/or by using the Smith chart and transmission line techniques explained in Chapter 3. Smith chart and transmission line techniques will be expanded in the microwave amplifiers which will be designed in Chapter 7. Summary. The calculated parameters of Example 6.17 are: • C = 0.87 • MAG = 24.12 dB • conjugate input admittance = (46.57 – j38.76) mS • conjugate output admittance = (2.55 – j4.61) mS • K = 4.45 6.5.4 Transducer gain (GT) Transducer gain (GT) of an amplifier stage is the gain achieved after taking into account the gain of the device and the actual input and output impedances used. This is the term most often used in r.f. amplifier design work. Transducer gain includes the effects of input and output impedance matching as well as the contribution that the transistor makes to the overall gain of the amplifier stage. Component resistive losses are neglected. Transducer gain (GT) can be calculated from: GT = ——————————— (6.29) |(yi + Ys)(yo + YL) – yf yr|2 312 High frequency transistor amplifiers where Ys and YL are respectively the source and load admittances used to terminate the Example 6.18 Find the gain of the circuit that was designed in Example 6.17. Disregard any component Solution. The transducer gain for the amplifier is determined by substituting the values given in Example 6.17 into Equation 6.29: GT = ——————————— |(yi + Ys)(yo + YL) – yf yr|2 4(46.57)(2.55)|130.50|2 × 10–12 = ———————————————————————————— |(63.94 – j27.48)(3.50 – j1.50) × 10–6 – (152.69 ∠ –160°) × 10–6|2 8 089 607.17 × 10–12 = ——————————————————————————————— |69.60 × 10–6 ∠ –23.26° × 3.81 × 10–6 ∠ –23.20° – 152.69 × 10–6 ∠ –160°|2 8 089 607.17 × 10–12 = ———————————————————— |265 × 10–6 ∠ –46.46° – 152.69 × 10–6 ∠ –160°|2 8 089 607.17 × 10–12 = ———————————————————————————— |182.55 × 10–6 – j192.10 × 10–6 – (–143.48 × 10–6 – j52.22 × 10–6)|2 8 089 607.17 × 10–12 = ———————————— |326.03 – j139.88|2 × 10–12 8 089 607.17 = ————————— = 64.28 or 18.08 dB |354.74 ∠ –23.22|2 The transistor gain calculated in Example 6.18 is approximately 6 dB less than the MAG that was calculated in Example 6.17. In this particular case, the reverse-transfer admittance (yr) of the transistor has taken an appreciable toll on gain. It is best to calculate GT imme- diately after the transistor’s load and source admittances are determined to see if the gain is sufficient for your purpose. If you cannot tolerate the lower gain, the alternatives are: • increase the operating current to increase gm and hopefully achieve more gain; • unilaterise or neutralise the transistor to increase gain (this is explained shortly); • find a transistor with a higher fT, to reduce the effect of yr. If you carry out one or more of the items above, you will have to go through all the calcu- lations in Examples 6.17 and 6.18 again. General r.f. design considerations 313 6.5.5 Designing amplifiers with conditionally stable transistors If the Linvill stability factor (C) calculated with Equation 6.22 is greater than 1, the tran- sistor chosen is potentially unstable and may oscillate under certain conditions of source and load impedance. If this is the case, there are several options available that will enable use of the transistor in a stable amplifier configuration: • select a new bias point for the transistor; this will alter gi and go; • unilaterise or neutralise the transistor; this is explained shortly; • mismatch the input and output impedance of the transistor to reduce stage gain. Alternative bias point The simplest solution is probably a new bias point, as any change in a transistor’s biasing point will affect its r.f. parameters. If this approach is taken, it is absolutely critical that the bias point be temperature-stable over the operational temperature range especially if C is close to unity. Unilaterisation and neutralisation Unilaterisation consists of providing an external feedback circuit (Cn and Rn in Figure 6.36) from the output to the input. The external current is designed to be equal but oppo- site to the internal yr current so that the net current feedback is zero. Stated mathematically, I(R C ) = –I(y ) and the effective composite reverse-transfer admittance is zero. With this n n r condition, the device is unconditionally stable. This can be verified by substituting yr = 0 in Equation 6.22. The Linvill stability factor in this case becomes zero, indicating uncon- ditional stability. One method of applying unilaterisation is shown in Figure 6.36(a). The principle of operation is explained in Figure 6.36(b). Referring to the latter figure, Vt is the total volt- age across the tuned circuit, n1 and n2 form the arms of one side of the bridge while Cn and Rn (external components) and the yr components (Rr and Cr) form the other arm of the bridge. Cn and Rn are adjusted until the bridge is balanced for zero feedback, i.e. VBE = 0. It follows that at balance Fig. 6.36 (a) Transformer unilaterisation circuit Fig. 6.36 (b) Equivalent unilaterisation circuit 314 High frequency transistor amplifiers n2 Zr VEC = ———— Vt = ——— Vt n1 + n2 Zr + Zn and after cross-multiplication Zn = Zr —— (6.30) Often when yr is a complex admittance consisting of gr ± jbr, it becomes very difficult to provide the correct external reverse admittance needed to totally eliminate the effect of yr. In such cases neutralisation is often used. Neutralisation is similar to unilaterisation except that only the imaginary component of yr is counteracted. An external feedback path is constructed as before, from output to input such that Bf = br (n1/n2). Thus, the compos- ite reverse-transfer susceptance is effectively zero. Neutralisation is very helpful in stabil- ising amplifiers because in most transistors, gr is negligible when compared to br. The effective cancellation of br very nearly cancels out yr. In practical cases, you will find that neutralization is used instead of unilaterisation. However, be warned: the addition of exter- nal components increases the costs and the complexity of a circuit. Also, most neutralisa- tion circuits tend to neutralise the amplifier at the operating frequency only and may cause problems (instability) at other frequencies. Summing up, unilaterisation/neutralisation is an effective way of minimising the effects of yr and increasing amplifier gain, but it costs more and is inherently a narrow-band compensation method. Mismatching techniques A more economical method stabilising an amplifier is to use selective mismatching. Another look at the Stern stability factor (K) in Equation 6.23 will reveal how this can be done. If Gs and GL are made large enough to increase the numerator sufficiently, it is pos- sible to make K greater than 1, and the amplifier will then become stable for those termi- nations. This suggests selectively mismatching the transistor to achieve stability. The price you pay is that the gain of the amplifier will be less than that which would have been pos- sible with a simultaneous conjugate match. Procedure for amplifier design using conditionally stable The procedure for a design using conditionally-stable devices is as follows. 1 Choose Gs based on some other criteria such as convenience of input-network, Q factor. Alternatively, from the transistor’s data sheet, choose Gs to be that value which gives you transistor operation with minimal noise figure. 2 Select a value of K that will assure a stable amplifier (K > 1). 3 Substitute the above values for K and Gs into Equation 6.2. and solve for GL. 4 Now that Gs and GL are known, all that remains is to find Bs and BL. Choose a value of BL equal to –bo of the transistor. The corresponding YL which results will then be very close to the true YL that is theoretically needed to complete the design. 5 Next calculate the transistor input admittance (Yin) using the load chosen in step 4 and Equation 6.19: General r.f. design considerations 315 y12 y21 yin = y11 – ———— y22 + YL where YL = GL ± jBL (found in steps 3 and 4). 6 Once Yin is known, set bs equal to the negative of the imaginary part of Yin or Bs = –Bin. 7 Calculate the gain of the stage using Equation 6.29. From this point forward, it is only necessary to produce input and output admittance networks that will present the calculated Ys and YL to the transistor. Example 6.19 shows how the procedure outlined above can be carried out. Example 6.19 A transistor has the following y-parameters at 200 MHz: yi = 2.25 + j7.2 yr = 0.70 /–85.9° yf = 44.72 /–26.6° yo = 0.4 + j1.9 All of the above parameters are in mS. Find the source and load admittances that will assure you of a stable design. Find the gain of the amplifier. Given: yi = 2.25 + j7.2 yr = 0.70 /–85.9° yf = 44.72 /–26.6° yo = 0.4 + j1.9 Required: (a) Load admittance, (b) source admittance and (c) gain when the circuit is designed for a Stern stability factor (K) of 3. Solution. If you were to use Equation 6.22 to calculate the Linvill stability factor (C) for the transistor, you will find C = 2.27. Therefore the device is potentially unstable and you must exercise extreme caution in choosing source and load admittances for the transistor. 1 The data sheet for the transistor states that the source resistance for optimum noise figure is 250 W. Choosing this value results in Gs = 1/Rs = 4 mS. 2 For an adequate safety margin choose a Stern stability factor of K = 3. 3 Substituting GS and K into Equation 6.23 and solving for GL yields 2(gi + GS)(go + GL) K = ————————— |yf yr| + Re(yf yr) (2)(2.25 + 4)(0.4 + GL) 3 = ——————————— |31.35| + Re(–12) GL = 4.24 mS 4 Setting BL = –bo of the transistor BL = –j1.9 mS The load admittance is now defined as YL = (4.24 – j1.9) mS 316 High frequency transistor amplifiers 5 The input admittance of the transistor is calculated using Equation 6.19: y12 y21 yin = y11 – ———— y22 + YL (0.701 ∠ –85.9°)(44.72 ∠ –26.6°) = 2.25 + j7.2 – —————————————— 0.4 + j1.9 + 4.24 – j1.9 = (4.84 + j13.44) mS 6 Setting Bs equal to the negative of the imaginary part of Yin, yields Bs = –j13.44 mS The source admittance needed for the design is now defined as: Ys = (4 – j13.44) mS 7 Now that Ys and YL are known, we can use Equation 6.29 to calculate the gain of the GT = ——————————— |(yi + Ys)(yo + YL) – yf yr|2 = ———————————————— |(6.25 – j6.24)(4.64) – (–12 – j28.96)|2 135 671.7 = ————— = 80.71 or 19.1 dB Therefore even though the transistor is not conjugately matched, you can still realise a respectable amount of gain while maintaining a stable amplifier. After you have satisfied yourself with the design, you need to design networks which will give the transistor its required source and load impedances and, within reason, also its operating bandwidth. This can be done by using the filter and matching techniques described in Part 5 and/or by using Smith chart and transmission line techniques explained in Part 3. Smith chart and transmission line techniques will be expanded in the microwave amplifiers which will be designed in Part 7. 6.6 Transistor operating configurations 6.6.1 Introduction Sometimes you will find that you want one set of y-parameters (e.g. common base para- meters) while the manufacturer has only supplied y-parameters for the common emitter configuration. What do you do? Well, you simply use the indefinite admittance matrix to convert from one set of parameters to another. Transistor operating configurations 317 6.6.2 The indefinite admittance matrix Admittance parameters provide an easy way of changing the operating configuration of a transistor. For example, if y-parameters for the common emitter configuration are known, it is easy to derive the parameters for common base and common collector configurations. These derivations are carried out using the indefinite admittance matrix method. The use of this matrix is best shown by example but to avoid confusion in the discussions which follow, it is best to first clarify the meaning of the suffixes attached to y-parameters. Each y-parameter is associated with two sets of suffixes. The first set, yi, yr, yf and yo, refer to y11, y12, y21, y22 respectively. (The symbols i, r, f, and o stand for input, reverse transconductance, forward transconductance and output respectively.) The second set, e, b, c, refer to the emitter, base or collector configuration respectively. For example, yie refers to y11 in the common emitter mode, yrb refers to y12 in the common base mode, yfc refers to y21 in the common collector mode and so on. An admittance matrix for a transistor is made as follows. 1 Construct Table 6.2. 2. Insert the appropriate set of y-parameters into the correct places in the table. If the common emitter parameters for a transistor are: yie = (13.75 + j13.95) × 10–3 S yre = (–0.15 – j1.15) × 10–3 S yfe = (1.09 – j17.51) × 10–3 S yoe = (0.30 + j1.57) × 10–3 S This set should be inserted as shown in Table 6.3. Note: No entries are made in the emitter row and column. Similarly, if a set of common base parameters is used instead, no entries will be made in the base row and column. The same applies for a set of common collector parameters; no entries are made in the collector row and column. 3. Sum real and imaginary parts of all rows and columns to zero. See Table 6.4. 4. Extract the required set of parameters. Table 6.2 Blank indefinite admittance matrix Base Emitter Collector Table 6.3 Indefinite admittance matrix with common emitter entries Base Emitter Collector Base (13.75 + j13.95)10–3 S (–0.15 – j1.15)10–3 S Collector (1.09 – j1.75)10–3 S (0.30 + j1.57)10–3 S Table 6.4 Indefinite admittance matrix with rows and columns summed to zero Base Emitter Collector Base (13.75 + j13.95)10–3 S (–13.60 – j12.80)10–3 S (–0.15 – j1.15)10–3 S Emitter (–14.84 – j12.20)10–3 S (14.99 + j12.62)10–3 S (–0.15 – j0.42)10–3 S Collector (1.09 – j1.75)10–3 S (–1.39 + j0.18)10–3 S (0.30 + j1.57)10–3 S 318 High frequency transistor amplifiers To obtain the y-parameters for the common base configuration, ignore all data in the base row and base column but extract the remaining four parameters. These are: yib = (14.99 + j12.62) × 10–3 S yrb = (–0.15 – j0.42) × 10–3 S yfb = (–1.39 + j0.18) × 10–3 S yob = (0.30 + j1.57) × 10–3 S To obtain the y-parameters for the common collector configuration, ignore all data in the collector row and collector column but extract the remaining four parameters. These yic = (13.75 + j13.95) × 10–3 S yrc = (–13.60 – j12.80) × 10–3 S yfc = (–14.84 – j12.20) × 10–3 S yoc = (14.99 + j12.62) × 10–3 S This information can now be applied to the general Equations 6.18 to 6.21 and subsequent The information given above has been shown for a bi-polar transistor but the method is general and applies to other transistor types as well. For FETS, replace the words base, emitter and collector in Tables 6.2 to 6.4 by gate, source and drain respectively. Example 6.20 A transistor operating with the d.c. conditions of VCE = 5 V, IC = 2 mA and at a frequency of 500 MHz is stated by the manufacturer to have the following y-parameters in the common emitter mode. y11 = (16 + j12) mS y12 = 1.55 mS ∠ 258° y21 = 45 mS ∠ 285° y22 = (0.19 + j6) mS Calculate its equivalent y-parameters for the base configuration when the transistor is oper- ating with the same d.c. operating conditions and at the same frequency. Solution. We will use the indefinite admittance matrix but, before doing so, the parame- ters y12 and y21 must be converted from its polar form: y12 = 1.55 mS ∠ 258° = (–0.32 – j1.52) mS y21 = 45 mS ∠ 285° = (11.65 – j43.47) mS Fill in the indefinite admittance matrix and sum all rows and columns to zero results in Table 6.5. Table 6.5 Base (mS) Emitter (mS) Collector (mS) Base (16 + j12) (–15.68 – j10.48) (–0.32 – j1.52) Emitter (–27.65 + 31.47) (27.52 – j26.99) (0.13 – j4.48) Collector (11.65 – j43.47) (–11.84 + j37.47) (0.19 + j6) Extracting the common base parameters yields: yib = (27.52 – j26.99) mS yrb = (0.13 – j4.48) mS yfb = (–11.84 + j37.47) mS yob = (0.19 + j6) mS Summary 319 6.7 Summary In Chapter 6, we have reviewed the operating principle of bi-polar transistors FETs and MOSFETs. We have also reviewed some transistor biasing methods. A brief resumé of a.c. equivalent circuits was introduced. Admittance parameters (y) were re-introduced, derived and applied to the design of amplifiers. You were shown methods on how to design ampli- fiers, conjugate matched amplifiers and amplifiers using conditionally-stable transistors. Our software program, PUFF, has no facilities for employing y-parameters directly. However, if you want, you can use Table 3.1 of Chapter 3 to convert all the y-parameters (or at least the results) into s-parameters. You can then use the PUFF techniques of Chapter 7 for amplifier design. Details of this technique are explained in Examples 7.1 and 7.2 followed by its PUFF design results in Figure 7.4 in the next chapter. Microwave amplifiers 7.1 Introduction In Part 2, we introduced transmission lines. Part 3 was devoted to Smith charts and scat- tering parameters while Part 4 covered the use of PUFF as a computing aid. In Part 5, we discussed the behaviour of passive devices such as capacitors and inductors at radio frequencies and investigated the use of these elements in the design of resonant tuned circuits, filters, transformers and impedance matching networks. We showed how the indefinite admittance matrix can be used to convert transistor parameters given in one configuration to another configuration. In Chapter 6, we investigated biasing techniques, the a.c. equivalent circuit of transistors, admittance parameters, and their use in high frequency amplifier design. We will now combine all of this information and use it in the design of microwave amplifiers. 7.1.1 Aim The main aim of this chapter is to show how microwave amplifiers can be designed using scattering parameters. 7.1.2 Objectives After you have read this chapter, you should be able to: • calculate transistor stability; • calculate maximum available gain of an amplifying device; • design amplifiers with conjugate matching impedances; • design amplifiers using conditionally stable transistors; • design amplifiers for a specific gain; • understand and calculate stability circles; • design amplifiers for optimum noise figure; • understand broadband matching amplifier techniques; • design broadband amplifiers; • understand feedback amplifier techniques; • design feedback amplifiers. Transistors and S-parameters 321 7.2 Transistors and s-parameters 7.2.1 Introduction The purpose of this section is to show you how s-parameters can be used in the design of transistor amplifiers. It has already been shown that transistors can be characterised by their s-parameters. Smith charts have been introduced, therefore it is now time to apply these parameters to produce practical design amplifiers. 7.2.2 Transistor stability Before designing a circuit, it is important to check whether the active device which we will use is (i) unconditionally stable or (ii) conditionally stable. This is necessary because different conditions require the appropriate design method. It is possible to calculate potential instabilities in transistors even before an amplifier is built. This calculation serves as a useful aid in finding a suitable transistor for a particular application. To calculate a transistor’s stability with s-parameters, we first calculate an intermediate quantity Ds where Ds = s11s22 – s12s21 (7.1) We do this because in the expressions that follow, you will find that the quantity Ds is used many times and we can save ourselves considerable work by doing this. The Rollett stability factor (K) is calculated as: 1 + |Ds| 2 – |s11| 2 – |s22| 2 K = —————————— (7.2) (2)(|s21|) (|s12|) If K is greater than 1, the transistor is unconditionally stable for any combination of source and load impedance. If K is less than 1, the transistor is potentially unstable and will most likely oscillate with certain combinations of source and load impedances. With K less than 1, we must be extremely careful in choosing source and load impedances for the transistor. It does not mean that the transistor cannot be used for a particular applica- tion; it merely indicates that the transistor will have to be used with more care. If K is less than 1, there are several approaches that we can take to complete the design: • select another bias point for the transistor; • choose a different transistor; • design the amplifier heeding carefully detailed procedures that we will introduce shortly. 7.2.3 Maximum available gain The maximum gain we can ever get from a transistor under conjugately matched condi- tions is called the maximum available gain (MAG). Maximum available gain is calcu- lated in two steps. (1) Calculate an intermediate quantity called B1, where B1 = 1 + |s11| 2 – |s22| 2 – |Ds| 2 (7.3) Ds is calculated from Equation 7.1. 322 Microwave amplifiers Note: The reason B1 has to be calculated first is because its polarity determines which sign (+ or –) to use before the radical in Equation 7.4 which follows shortly. (2) Calculate MAG using the result from Equation 7.2: MAG = 10 log + 10 log K ± K 2 − 1 (7.4) MAG = maximum available gain in dB K = stability factor from Equation 7.2 Note: K must be greater than 1 (unconditionally stable) otherwise Equation 7.4 will be undefined because the radical sign will become an imaginary number rendering the equa- tion invalid. Thus, MAG is undefined for unstable transistors. 7.3 Design of amplifiers with conjugately matched impedances This method of design is only applicable to transistors which are stable and give sufficient gain for our design aims. For other conditions we will have to use other design methods. This design procedure results in load and source reflection coefficients which provide a conjugate match for the actual output and input impedances of the transistor. However, remember that the actual output impedance of a transistor is dependent on its source impedance and vice-versa. This dependency is caused by the reverse gain (s12) of the tran- sistor. If s12 was zero, then of course the load and source impedances would have no effect on the transistor’s input and output impedances. 7.3.1 Output reflection coefficient To find the desired load reflection coefficient for a conjugate match C2 = s22 – (Ds s11*) (7.5) where the asterisk indicates the complex conjugate of s11 (same magnitude but opposite angle). The quantity Ds is the quantity calculated in Equation 7.1. Next we calculate B2: B2 = 1 + |s22| 2 – |s11| 2 – |Ds| 2 (7.6) The magnitude of the reflection coefficient is found from the equation B2 ± B2 − 4 C2 (7.7) ΓL = 2 C2 The sign preceding the radical is opposite to the sign of B2 previously calculated in Equation 7.6. The angle of the load reflection coefficient is simply the negative of the angle of C2 calculated in Equation 7.5. Design of amplifiers with conjugately matched impedances 323 After the desired load reflection coefficient is found, we can either (a) plot GL on a Smith chart to find the load impedance (Z) directly, or (b) substitute GL from the equation ZL – Zo GL = ———— (7.8) ZL + Zo You have encountered the above equation in Chapter 2 when we were looking at trans- mission lines. 7.3.2 Input reflection coefficient With the desired load reflection coefficient specified, the source reflection coefficient needed to terminate the transistor’s input can now be calculated: ⎡ s s Γ ⎤ Γs = ⎢s11 + 12 21 L ⎥ (7.9) ⎣ 1 − s22 ΓL ⎦ The asterisk sign again indicates the conjugate of the quantity in brackets (same magni- tude but opposite sign for the angle). In other words, once we complete the calculation within brackets of Equation 7.9, we will have the correct magnitude but the incorrect angle sign and will have to change the sign of the angle. As before when Gs is found, it can be plotted on a Smith chart or we can again use the Zo – Zs Gs = – —— —— (7.10) Zo + Zs All the foregoing is best clarified by an example. Example 7.1 A transistor has the following s-parameters at 150 MHz with a Vce = 12 V and Ic = 8 mA: s11 = 0.3 ∠ 160° s12 = 0.03 ∠ 62° s21 = 6.1 ∠ 65° s22 = 0.40 ∠ –38° The amplifier must operate between 50 W terminations. Design (a) input and (b) output matching networks for simultaneously conjugate matching of the transistor for maximum Given: ƒ = 150 MHz, Vce = 12 V, Ic = 8 mA, s11 = 0.3 ∠ 160°, s12 = 0.03 ∠ 62°, s21 = 6.1 ∠ 65°, s22 = 0.40 ∠ –38°. Required: Conjugate input and output matching networks for maximum gain to 50 W source and load impedances. Solution. Using Equations 7.1 and 7.2, check for stability: Ds = s11s22 – s12s21 = (0.3 ∠ 160°)(0.4 ∠ – 38°) – (0.03 ∠ 62°)(6.1 ∠ 65°) = (0.120 ∠ 122°) – (0.183 ∠ 127°) 324 Microwave amplifiers = (–0.064 + j0.102) – (–0.110 + j0.146) = (0.046 – j0.044) = (0.064 ∠ –43.73°) Using the magnitude of Ds, calculate K: 1 + |Ds| 2 – |s11| 2 – |s22| 2 K = —————————— 1 + (0.064) 2 – (0.3)2 – (0.4)2 = ———————————— = 2.06 Since K > 1, the transistor is unconditionally stable and we may proceed with the design. Using Equation 7.3, calculate B1: B1 = 1 + |s11| 2 – |s22| 2 – |Ds| 2 B1 = 1 + (0.3)2 – (0.4)2 – (0.064)2 = 0.926 Using Equation 7.4, calculate maximum available gain (MAG): MAG = 10 log + 10 log K ± K 2 − 1 Since B1 is positive, the negative sign will be used in front of the square root sign and MAG = 10 log + 10 log 2.06 − (2.06)2 − 1 = 23.08 + ( −5.87) = 17.21 dB We will consider 17.21 dB to be adequate for our design gain of 16 dB minimum. If the design had called for a minimum gain greater than 16 dB, a different transistor would be To find the load reflection coefficient for a conjugate match, the two intermediate quan- tities (C2 and B2) must first be found. Using Equation 7.5: C2 = s22 – (Dss11*) = (0.4 ∠ –38°) – [(0.064 ∠ –43.73°) (0.3 ∠ –160°) ] = 0.315 – j0.246 – [–0.018 + j0.008] = (0.419 ∠ –37.33°) Using Equation 7.6 B2 = 1 + |s22| 2 – |s11| 2 – |Ds| 2 = 1 + (0.4)2 – (0.3)2 – (0.064)2 = 1.066 Therefore the magnitude of the load reflection coefficient can now be found using Equation 7.7: Design of amplifiers with conjugately matched impedances 325 B2 ± B2 − 4 C2 ΓL = 2 C2 1.066 − (1.066)2 − 4(0.419)2 = 0.486 The angle of the load reflection coefficient is simply equal to the negative of the angle of C2 or +37.33°. Thus GL = 0.486 ∠ 37.33° GL can now be substituted in Equation 7.9 to calculate Gs: s12s21 GL * Gs = s11 + ———— 1 – s22 GL ] (0.03 ∠ 62°)(6.1 ∠ 65°)(0.486 ∠ 37.33°) * [ 0.3 ∠ 160° + ————————————————— 1 – (0.4 ∠ –38°)(0.486 ∠ 37.33°) ] (0.089 ∠ 164.33°) * = (–0.282 + j0.103) + ————————— (1 – 0.194 ∠ –0.670°) ] (0.089 ∠ 164.33°) * = (–0.282 + j0.103) + ———————— (0.806 ∠ 0.142°) = [(–0.282 + j0.103) + (–0.160 + j0.030)]* = [0.463 ∠ 163.29°]* = 0.463 ∠ –163.29° Once the desired Gs and GL are known, all that remains is to provide the transistor with components which ‘look like’ Gs and GL. (a) Input matching network. The input matching network design is shown on the Smith chart of Figure 7.1. The object of the design is to force the 50 Ω source to present a reflec- tion coefficient1 of 0.463 ∠ –163.29° to the transistor input. With Gs plotted as shown, the corresponding desired and normalised impedance is read directly from the chart as Z s = (0.36 – j0.12) Ω. Remember this is a normalised impedance because the chart has been normalised to 50 Ω. The actual impedance represented by Gs is equal to 50(0.36 – j0.12) Ω = (18.6 – j6) Ω. Now we must transform the 50 Ω source to (18.6 – j6) Ω impedance. The most common circuit used is a low pass filter configuration consisting of a shunt C and a series 1 In all examples containing reflection coefficients and Smith charts, the reflection coefficients are plotted on the Smith chart and the resultant values are read from it. Theoretically, the Smith chart should give you an exact answer. In practice, reading difficulties and interpolations must be made, so expect slightly different answers if you are using mathematics to derive these values. Strictly speaking, this is not a problem because transistor char- acteristics change, even when the same type number is used. Hence perfect match with one transistor does not mean perfect match with another transistor. The most difficult part of amplifier design is choosing loads that will produce the same circuit characteristics in spite of transistor changes. 326 Microwave amplifiers Fig. 7.1 Input matching network A = 1 + j0, B = 0.43 – j0.5, C = 0.43 – j0.14 L. Remember that when using a Smith chart with shunt elements, you use it as an admit- tance chart, and when using the chart for series elements, you use it as an impedance chart. For ease of transformation, we use the Smith chart type ZY-10-N which was introduced in Chapter 3. Proceeding from the source, we have: Arc AB = shunt C = j1.33 S Arc BC = series L = j0.34 Ω If you have difficulty following the above construction, look first at Figure 7.3 where you will see the schematic of the amplifier. It starts off with a 50 Ω source (point A on Figure 7.1). Across this point, we have a shunt capacitor; therefore we must use the admittance part of the chart. This shunt capacitance moves us to point B in Figure 7.1, i.e. along arc AB. The next element in Figure 7.1 is a series inductor. We must therefore use the imped- ance part of the Smith chart in Figure 7.1. Our final destination is the required source Design of amplifiers with conjugately matched impedances 327 impedance for transistor (point C in Figure 7.1) – hence the arc BC. The Smith chart values are read according to the part of the chart being used; admittance values for the shunt components and impedance values for the series components. The actual component values are found using Equations 7.11 to 7.14 which are: Cseries = ——— (7.11) ω XN Cshunt = —— (7.12) L series = —— (7.13) Lshunt = —— (7.14) N = normalisation value B = susceptance in Siemens X = reactance in ohms w = frequency in radians/second For this example C1 = ———————— = 28.22 pF ≈ 28 pF 2p(150 MHz)(50) L1 = —————— = 18.04 nH ≈ 18 nH 2p(150 MHz) This completes the input matching network. (b) Output matching network. The load reflection coefficient is plotted in Figure 7.2 and after plotting in GL = 0.486 ∠ 37.33° the Smith chart shows a normalised load imped- ance of (1.649 + j1.272) Ω. After re-normalisation, it represents a load impedance ZL = 50 (1.649 + j1.272) Ω or (82.430 + j63.611) Ω. The matching network is designed as follows. Proceeding from the load: Arc AB = series C = –j1.1 Ω Arc BC = shunt L = –j0.8 S If you have difficulty with the Smith chart, look at the schematic on Figure 7.3. The final load is 50 Ω (point A in Figure 7.2). The transistor load is point C in Figure 7.2. 328 Microwave amplifiers Fig. 7.2 Output matching network A = 1 + j0, B = 1 –j1.28, C = 0.486 ∠ 37.33° or 1.65 + j1.272 Starting from the 50 Ω point (point A in Figure 7.2), you encounter a series capacitor. Therefore the series part of the chart must be used. This takes you to point B on the chart, along arc AB. Next you have a shunt inductor (see Figure 7.3); therefore you must use the admittance part of the chart to get to your destination (point C), that is along arc BC in Figure 7.2. The Smith chart values are read according to the part of the chart being used; admittance values for the shunt components and impedance values for the series components. The actual component values are found using Equations 7.11 and 7.14 which are for this example: C2 = ————————— = 19.29 pF ≈ 19 pF 2 p(150 MHz)(1.1)(50) Design of amplifiers with conjugately matched impedances 329 Fig. 7.3 R.F. circuit for Example 7.1 L2 = ———————— = 66.31 nH ≈ 66 nH 2 p(150 MHz)(0.8) The completed design (minus biasing network) is shown in Figure 7.3. Transducer gain (GT) The transducer gain is the actual gain of an amplifier stage including the effects of input and output matching and device gain. It does not include losses attributed to power dissi- pation in imperfect components. Transducer gain is calculated as follows: |s21|2(1 – |Gs|2)(1 – |GL|2) GT = ————————— ———— ——— (7.15) |(1 – s11Gs)(1 – s22GL) – s12s21GLGs|2 Gs and GL are the source and load reflection coefficients respectively Calculation of GT is a useful method of checking the power gain of an amplifier before it is built. This is shown by Example 7.2. Example 7.2 Calculate the transducer gain of the amplifier that was designed in Example 7.1. Given: As in Example 7.1. Required: Transducer gain. Solution. Using Equation 7.15 |s21|2(1 – |Gs|2)(1 – |GL|2) GT = ——————————————— |(1 – s11Gs)(1 – s22GL) – s12s21GLGs|2 (6.1)2(1 – (0.463)2)(1 – (0.486)2) = ——————————————————————————————————————————— |(1 – 0.139 ∠ 3.3°)(1 – 0.194 ∠ 01.7°) – (0.03 ∠ 62°)(6.1 ∠ 65°)(0.486 ∠ 37.33°)(0.463 ∠ –163.29°)|2 22.329 22.329 ≈ ——————————— = ———————————— |0.694 – (0.041 ∠ 1.04°)|2 |0.694 – (0.041 + j0.001)|2 330 Microwave amplifiers = ——— = 52.365 or 17.19 dB Note: The transducer gain calculates to be very close to MAG. This is due to the fact that s12 is not equal to zero and is therefore providing some internal transistor feedback. PUFF results The results of Examples 7.1 and 7.2 using PUFF are shown in Figure 7.4. However, you should be aware of how PUFF was modified for the results. • The amplitude range and the frequency range in the rectangular plot had to be modified as explained in Chapter 4 to obtain the required amplitude and frequency ranges. • There is no transistor device in PUFF that meets the requirements of the transistor in the examples. A new transistor template called ‘ed701’ was generated by copying the FHX04.device template and modifying it to suit the requirements of the example. • A resistor of 1 pΩ was generated within PUFF to provide a spacer for ease in laying out the circuit. • The input matching circuit of Figure 7.1 was plotted at port 1. At the match frequency, the input match reflection coefficient is shown as –35.39 dB in Figure 7.4. • The output matching circuit of Figure 7.2 was plotted at port 2. At the match frequency, Fig. 7.4 Results of Examples 7.1 and 7.2 using PUFF Design of amplifiers with conjugately matched impedances 331 the output match reflection coefficient is shown as –21.21 dB in Figure 7.4. • The gain of the circuit is given by PUFF as 17.13 dB. We calculated the gain as 17.19 dB. Note: There is a very slight discrepancy between the results but this is to be expected because the examples were carried out graphically. Nonetheless, this should convince you that our design methods are reliable! Example 7.3 A MESFET has the following S-parameters at 5 GHz with Vce = 15 V and Ic = 10 mA: s11 = 0.3 ∠ 140° s12 = 0.03 ∠ 65° s21 = 2.1 ∠ 62° s22 = 0.40 ∠ –38° Calculate the maximum available gain (MAG) for the transistor under these operating Given: ƒ = 5 GHz, Vce = 15 V, Ic = 10 mA, s11 = 0.3 ∠ 140°, s12 = 0.03 ∠ 65°, s21 = 2.1 ∠ 62°, s22 = 0.40 ∠ –38°. Required: MAG for the MESFET at 5 GHz. Solution. Using Equations 7.1 and 7.2, check for stability: Ds = s11s22 – s12s22 = (0.3 ∠ 140°)(0.4 ∠ –38°) – (0.03 ∠ 65°)(2.1 ∠ 62°) = (0.120 ∠ 102°) – (0.063 ∠ 127°) = (–0.025 + j0.117) – (–0.038 + j0.050) = (0.013 + j0.067) = (0.068 ∠ 79.06°) Using the magnitude of Ds, calculate K: 1 + |Ds|2 – |s11|2 – |s22|2 K = —————————— (2)(|s21|) (|s12|) 1 + (0.068)2 – (0.3)2 – (0.4)2 = ———————————— = 5.99 Since K > 1, the transistor is unconditionally stable and we may proceed with the design. Using Equation 7.3, calculate B1: B1 = 1 + |s11|2 – |s22|2 – |Ds|2 = 1 + (0.3)2 – (0.4)2 – (0.068)2 = 0.925 Using Equation 7.4, calculate maximum available gain (MAG): Since B1 is positive, the negative sign will be used in front of the square root sign: MAG = 10 log + 10 log K ± K 2 − 1 332 Microwave amplifiers If you wish, check the answer by using PUFF. MAG = 10 log + 10 log 5.99 − (5.99)2 − 1 = 18.45 + ( −10.75) ≈ 7.7 dB Example 7.4 An integrated circuit has the following S-parameters: s11 = 0.3 ∠ 140° s12 = 0.03 ∠ 65° s21 = 2.1 ∠ 62° s22 = 0.40 ∠ –38° If its source reflection coefficient Gs = 0.463 ∠ –164° and its load reflection coefficient GL = 0.486 ∠ 38°, calculate the transducer gain of the amplifier. Given: Gs = 0.463 ∠ –140° GL = 0.486 ∠ 38° s11 = 0.3 ∠ 140° s12 = 0.03 ∠ 65° s21 = 2.1 ∠ 62° s22 = 0.40 ∠ –38° Required: Amplifier transducer gain. Solution. Using Equation 7.15 |s21|2(1 – |Gs|2)(1 – |GL|2) GT = ——————————————— |(1 – s11Gs)(1 – s22GL) – s12s21GLGs|2 (2.1)2(1 – (0.463)2)(1 – (0.486)2) = ————————————————————————————————— |(1 – 0.139)(1 – 0.194) – (0.03 ∠ 65°)(2.1 ∠ 62°)(0.486 ∠ 38°)(0.463 ∠ –140°)|2 2.646 2.646 = ——————— ———— = ——————————— |0.694 – (0.014 ∠ 25°)| 2 |0.694 – (0.014 – j0.002)|2 = ——— = 5.708 or 7.6 dB If you wish, check the answer by using PUFF. 7.4 Design of amplifiers for a specific gain In cases where a specific gain is required, it is normal practice to provide selective mismatching so that transistor gain can be reduced to the desired gain. Selective mismatching is a relatively inexpensive method used to decrease gain by not matching a transistor to its conjugate load. One of the easiest ways of selective mismatching is through the use of a constant gain circle plotted on the Smith chart. A constant gain circle is merely a circle, the circumfer- ence of which represents a locus of points (load impedances) that will force the amplifier Design of amplifiers for a specific gain 333 gain to a specific value. For instance, any of the infinite number of impedances located on the circumference of a 12 dB constant gain circle would force the amplifier stage gain to 12 dB. Once the circle is drawn on a Smith chart, you can see the load impedances that will provide a desired gain. 7.4.1 Constant gain circles To plot a constant gain circle on a Smith chart, it is necessary to know (i) where the centre of the circle is located and (ii) its radius. The procedure for calculating a constant gain circle is as follows. 1 Calculate Ds as in Equation 7.1. 2 Calculate D2: D2 = |s22|2 – |Ds|2 (7.16) 3 Calculate C2: C2 = s22 – Dss11* (7.17) 4 Calculate G: |desired gain| G = —————— (7.18) 5 Calculate centre location of constant gain circle: 6 Calculate radius of the circle: GC2 (7.19 ro = 1 + D2 G Equation 7.19 produces a complex number in magnitude–angle format similar to that of a 1 − 2 K s12 s21 G + s12 s21 G 2 po = (7.20 1 + D2 G reflection coefficient. This number is plotted on the Smith chart exactly as you would plot a value of reflection coefficient. The radius of the circle that is calculated with Equation 7.20 is simply a fractional number between 0 and 1 which represents the size of that circle in relation to a Smith chart. A circle with a radius of 1 has the same radius as a Smith chart; a radius of 0.5 represents half the radius of a Smith chart and so on. After the load reflection coefficient (in effect the load impedance) is chosen by the designer, the next step will be to determine the source reflection coefficient that is required to prevent any further decrease in gain. This value is of course the conjugate of the actual input reflection coefficient of the transistor with the specified load calculated by Equation 7.9. To clarify the procedure, we now present Example 7.5. 334 Microwave amplifiers Example 7.5 A transistor has the following S-parameters at 1 GHz, with Vce = 15 V and Ic = 5 mA: s11 = 0.28 ∠ –58° s12 = 0.08 ∠ 92° s21 = 2.1 ∠ 65° s22 = 0.8 ∠ –30° Design an amplifier to present 9 dB of gain at 1 GHz. The source impedance Zs = (35 – j60) Ω and the load impedance ZL = (50 – j50) W. The transistor is unconditionally stable with K = 1.168. Design the output and input networks. Given: ƒ = 1 GHz Vce = 15 V Ic = 5 mA s11 = 0.28 ∠ –58° s12 = 0.08 ∠ 92° s21 = 2.1 ∠ 65° s22 = 0.8 ∠ –30° Zs = (35 – j60) Ω ZL = (50 – j50) K = 1.168 Required: 9 dB amplifier, output network, input network. Solution. Using Equation 7.1, find Ds for substitution in Equations 7.16 and 7.17: Ds = s11s22 – s12s21 = (0.28 ∠ –58°)(0.8 ∠ –30°) – (0.08 ∠ 92°)(2.1 ∠ 65°) = (0.224 ∠ –88°) – (0.168 ∠ 157°) = 0.008 – j0.224 + 0.155 – j0.066 = 0.333 ∠ –60.66° Using Equation 7.16, find D2 for subsequent insertion in Equation 7.19: D2 = |s22|2 – |Ds|2 = (0.8)2 – (0.333)2 = 0.529 Using Equation 7.17, find C2 for subsequent insertion in Equation 7.19: C2 = s22 – Dss11* = (0.8 ∠ –30°) – (0.333 ∠ –60.66°)(0.28 ∠ 58°) = (0.693 – j0.400) – (0.093 – j0.004) = (0.719 ∠ –33.42°) Bearing in mind that a power ratio of 9 dB is a power ratio of 7.94, use Equation 7.18 to find G for subsequent insertion in Equation 7.19: |desired gain| 7.94 G = —————— = ——— = 1.80 |s21|2 (2.1)2 Using Equation 7.19, find the centre of the constant gain circle: GC2* 1.80 (0.719 ∠ 33.42°) ro = ———— = —————————— = 0.663 ∠ 33.42° 1 + D2G 1 + (0.529)(1.80) Using Equation 7.20, find the radius for the 9 dB constant gain circle: 1 − 2 K s12 s21 G + s12 s21 G 2 po = 1 + D2 G Design of amplifiers for a specific gain 335 1 − 2(1.168)(0.08)(2.1)(1.80) + (0.08 × 2.1)2 (1.80)2 1 + (0.529)(1.80) 1 − 0.706 + 0.091 1 + 0.952 = 0.318 The Smith chart construction is shown in Figure 7.5. Note that any load impedance located on the circumference of the circle will produce an amplifier gain of 9 dB if the input impedance of the transistor is conjugately matched. The actual load impedance we have to Fig. 7.5 Output network using 9 dB constant gain circle A = 1 – j1, B = 1 – j3, C = 0.1 – j0.11, ro = 0.663 ∠ 33.43°, po = 0.318. Angle between point D and E = 33.43° 336 Microwave amplifiers work with is (50 – j50) which in its normalised form is (1 – j1) Ω on the Smith chart and denoted by point A. Output network. The transistor’s output network must transform the actual load imped- ance into a value that falls on the constant gain 9 dB circle. Obviously there are many circuit configurations which will satisfy these conditions. The configuration shown in Figure 7.5 has been chosen for convenience. Proceeding from the load: Arc AB = series C = –j2.0 Ω Arc BC = shunt L = –j0.41 S Using Equation 7.11 for a series C: C1 = ———————— ≈ 1.6 pF 2p(1 GHz)(2)(50) Using Equation 7.14 for a shunt L: L1 = ———————— ≈ 19.4 nH 2p(1 GHz)(0.41) Input network. For a conjugate match at the input to the transistor with GL = 0.82 ∠ 13° (point C in Figure 7.5), the desired source reflection coefficient must be (using Equation s12s21 GL * Gs = [(s11 + ———— 1 – s22 GL ] (0.08 ∠ 92°)(2.1 ∠ 65°)(0.82 ∠ 13°) * [ 0.28 ∠ –58° + ——————————————— 1 – (0.8 ∠ –30°)(0.82 ∠ 13°) ] (0.138 ∠ 170.00°) * = 0.28 ∠ –58° + ———————— 1 – (0.656 ∠ –17°) ] (0.138 ∠ 170.00°) * = 0.148 – j0.237 + ———————— (0.420 ∠ 27.24°) ] = [0.148 – j0.237 + (–0.262 + j0.199]* = [0.120 ∠ –161.56°]* = 0.120 ∠ 161.56° The point is plotted as point D in Figure 7.6. The actual normalised source impedance is plotted at point A (0.7 – j1.2) Ω. The input network must transform the actual impedance at point A to the desired impedance at point D. We have used a three element matching network this time: Design of amplifiers for a specific gain 337 Fig. 7.6 Input network of Example 7.5 A = 0.7 – j1.2, B = 0.37 + j1.25, C = 0.2 + j0.33, D = 1.25 – j0.1 Arc AB = shunt C2 = j0.63 S Arc BC = series L2 = j1.08 Ω Arc CD = shunt C3 = j2.15 S Using Equation 7.12 for a shunt capacitance: C2 = ——————— ≈ 2 pF 2p(1 GHz)(50) Using Equation 7.13 for a series inductance: L2 = ————— ≈ 8.5 nH 2p(1 GHz) 338 Microwave amplifiers Fig. 7.7 R.F. circuit for Example 7.5 Using Equation 7.12 for a shunt capacitance: C3 = —————— ≈ 6.8 pF 2p(1 GHz)(50) The completed design (minus biasing network) is shown in Figure 7.7. Example 7.6 Use the information of Example 7.5 to calculate a constant gain circle of 8 dB. Given: ƒ = 1 GHz Vce = 15 V Ic = 5 mA s11 = 0.28 ∠ –58° s12 = 0.08 ∠ 92° s21 = 2.1 ∠ 65° s22 = 0.8 ∠ –30° Ds = 0.333 ∠ –60.66° D2 = 0.529° C2 = 0.719 ∠ –33.42° K = 1.168 Required: A constant gain circle of 8 dB. Solution. Bearing in mind that a power ratio of 8 dB is a power ratio of 6.31, use equa- tion 7.18 to find G for subsequent insertion in Equation 7.19: |desired gain| 6.31 G = —————— = ——— = 1.43 |s21| 2 (2.1)2 Using Equation 7.19, find the centre of the constant gain circle: GC2* 1.43(0.719 ∠ 33.42°) ro = ———— = ————————— = 0.585 ∠ 33.42° 1 + D2G 1 + (0.529)(1.43) Using Equation 7.20, find the radius for the 9 dB constant gain circle: 1 − 2 K s12 s21 G + s12 s21 G 2 po = 1 + D2 G Design of amplifiers for a specific gain 339 1 − 2(1.168)(0.08)(2.1)(1.43) + (0.08 × 2.1)2 (1.43)2 1 + (0.529)(1.43) 1 − 0.561 + 0.058 1 + 0.756 = 0.401 7.4.2 Design of amplifiers with conditionally stable devices When the Rollett stability factor (K) calculates to be less than unity, it is a certainty that with some combinations of source and load impedances, the transistor will oscillate. To prevent oscillation the source and load impedances must be chosen very carefully. One of the best methods of determining those source and load impedances that will cause the tran- sistor to go unstable is to plot stability circles on a Smith chart. 7.4.3 Stability circles A stability circle is simply a circle on a Smith chart which represents the boundary between those values of source or load impedance that cause instability and those that do not. The circumference of the circle represents the locus of points which forces K = 1. Either the inside or the outside of the circle may represent the unstable region and that determination must be made after the circles are drawn. The location and radii of the input and output stability circles are found as follows. 1 Calculate Ds using Equation 7.1. 2 Calculate C1: C1 = s11 – Dss22* (7.21) 3 Calculate C2 using Equation 7.5. 4 Calculate the centre location of the input stability circle: Gs1 = —————— (7.22) |s11|2 – |Ds|2 5 Calculate the radius of the input stability circle: | s12s21 ps1 = —————— |s11|2 – |Ds|2 | (7.23) 6 Calculate the centre location of the output stability circle: Gs2 = —————— (7.24) |s22|2 – |Ds|2 7 Calculate the radius of the output stability circle: | s11s21 ps2 = —————— |s22|2 – |Ds|2 | (7.25) 340 Microwave amplifiers Fig. 7.8 Unstable regions for a potentially unstable transistor Once the calculations are made, circles can be plotted directly on the Smith chart. For a potentially unstable transistor, the stability circles might resemble those shown in Figure After the stability circles are plotted on the chart, the next step is to determine which side of the stability circles (inside or outside) represents the stable region. This is easily done if s11 and s22 for the transistor are less than 1. If the stability circles do not enclose the centre of the Smith chart, then regions inside the stability circles are unstable and all regions outside the stability circles on the Smith chart are stable regions. See Figure 7.8. If one of the stability circles encloses the centre of the Smith chart, then the region inside that stability circle is stable. This is because the S-parameters were measured with a 50 Ω source and load, and since the transistor remained stable (s11 and s22 < |1|) under these conditions, then the centre of the Smith chart must be part of the stable regions. Example 7.7 will help to clarify this. Example 7.7 The S-parameters for a transistor at 200 MHz with Vce = 6 V and Ic = 5 mA are: s11 = 0.4 ∠ 280° s12 = 0.048 ∠ 65° s21 = 5.4 ∠ 103° s22 = 0.78 ∠ 345° Design and choose stable load and source reflection coefficients that will provide a power gain of 12 dB at 200 MHz. Given: ƒ = 200 MHz Vce = 6 V Ic = 5 mA s11 = 0.4 ∠ 280° s12 = 0.048 ∠ 65° s21 = 5.4 ∠ 103° s22 = 0.78 ∠ 345° Required: Stable load reflection coefficient, stable source reflection coefficient, and power gain of 12 dB at 200 MHz. Design of amplifiers for a specific gain 341 1 Using Equation 7.1, find Ds: Ds = s11s22 – s12s21 = (0.4 ∠ 280°)(0.78 ∠ 345°) – (0.048 ∠ 65°)(5.4 ∠ 103°) = (–0.027 – j0.311) – (–0.254 + j0.054) = (0.429 ∠ –58.2°) 2 Using Equation 7.2, calculate Rollett’s stability factor (K): 1 + |Ds|2 – |s11|2 – |s22|2 K = —————————— (2)(|s21|) (|s12|) 1 + (0.429)2 – (0.4)2 – (0.78)2 = ————————————— = 0.802 Since K < 1, we must exercise extreme care in choosing source and load impedances otherwise the transistor will oscillate so stability circles must be plotted. 3 Using Equation 7.21, calculate C1: C1 = s11 – Dss22* = (0.4 ∠ 280°) – (0.429 ∠ –58.2°)(0.78 ∠ –345°) = (0.069 – j0.394) – (0.244 – j0.229) = (0.241 ∠ –136.7°) 4 Using Equation 7.5, calculate C2: C2 = s22 – (Dss11*) = (0.78 ∠ 345°) – (0.429 ∠ –58.18°)(0.4 ∠ –280°) = (0.753 – j0.202) – (0.159 + j0.064) = 0.651 ∠ –24.1° 5 Using Equation 7.22, calculate the centre location of the input stability circle: Gs1 = —————— |s11|2 – |Ds|2 (0.241 ∠ 136.7°) = ———————— (0.4)2 – (0.429)2 = –10 ∠ 136.7° or 10 ∠ –43.4° 6 Using Equation 7.23, calculate the radius of the input stability circle: | s12s21 ps1 = —————— |s11|2 – |Ds|2 | 342 Microwave amplifiers (0.048 ∠ 65°)(5.4 ∠ 103°) = ———————————— (0.4)2 – (0.429)2 | = 10.78 7 Using Equation 7.24, calculate the centre location of the output stability circle: Gs2 = ————— |s22| 2 – |D |2 (0.651 ∠ 24.1°) = ———————— (0.78)2 – (0.429)2 = 1.534 ∠ 24.1° 8 Using Equation 7.25, calculate the radius of the output stability circle: | s12s21 ps2 = —————— |s22|2 – |Ds|2 | (0.048 ∠ 65°)(5.4 ∠ 103°) = ——————————— (0.78)2 – (0.429)2 | = 0.611 These circles are shown in Figure 7.9. Note that the input stability circle is so large that it is actually drawn as a straight line on the Smith chart. Since s11 and s22 are both < 1, we can deduce that the inside of the input stability circle represents the region of stable source impedances, while the outside of the output stability circle represents the region of stable load impedances for the device. The 12 dB gain circle is also shown plotted in Figure 7.9. It is found using Equations 7.1 and 7.16 to 7.20 in a manner similar to that given in Example 7.7. The centre location for the 12 dB gain circle is GO = 0.287 ∠ 24°. The radius for the 12 dB gain circle is po = The only load impedances we may not select for the transistor are located inside of the output stability circle. Any other load impedance located on the 12 dB gain circle will provide the needed gain provided the input of the transistor is conjugately matched and as long as the input impedance required for a conjugate match falls inside of the input stabil- ity circle. A convenient point on the 12 dB gain circle will be selected and for this example, we GL = 0.89 ∠ 70° Using Equation 7.9 to calculate the source reflection coefficient for a conjugate match and plotting this point on the Smith chart Gs = 0.678 ∠ 79.4° Design of amplifiers for a specific gain 343 Fig. 7.9 Stability parameters A = 1 + j0, GL = 0.89 ∠ 70°, GS = 0.678 ∠ 79.4°, Go = 0.287 ∠ 24° Notice that Gs falls within the stable region of the input stability circle and therefore repre- sents a stable termination for the transistor. The input and output matching networks are then designed in the manner detailed in Example 7.5. Example 7.8 In Example 7.7, the centre location for the 12 dB gain circle is given as ro = 0.287 ∠ 24° and the radius for the 12 dB circle is given as po = 0.724. Show that these values are Given: Values of Example 7.7. Required: ro and po. Solution. Bearing in mind that a power gain of 12 dB represents a power ratio of 15.85 and using Equation 7.18 344 Microwave amplifiers gain desired 15.85 G = —————— = ——— = 0.544 |s21|2 5.42 Using Equation 7.16, find D2 for subsequent insertion in Equation 7.19: D2 = |s22|2 – |Ds|2 = |0.78|2 – |0.429|2 = 0.424 Using Equation 7.19, find the centre of the constant gain circle: GC2* 0.544(0.651 ∠ 24.1°) ro = ———— = —————————— = 0.288 ∠ 24.1° 1 + D2G 1 + (0.424)(0.544) ≈ 0.287 ∠ 24° Using Equation 7.20, find the radius for the 12 dB constant gain circle: 1 − 2 K s12 s21 G + s12 s21 G 2 po = 1 + D2 G 1 − 2(0.802)(0.048)(5.4)(0.544) + (0.048 × 5.4)2 (0.544)2 1 + (0.424)(0.544) 1 − 0.266 + 0.020 1 + 0.231 = 0.724 Example 7.9 In Example 7.8, it is stated that Gs is 0.678 ∠ 79.4°. Show that this value is correct for a GL of 0.89 ∠ 70°. Given: Values of Example 7.8. Required: Gs. Solution. Using Equation 7.9 s12s21GL * Gs = s11 + ———— 1 – s22GL ] (0.048 ∠ 65°)(5.4 ∠ 103°)(0.89 ∠ 70°) * = 0.4 ∠ 280° + ———————————————— 1 – (0.78 ∠ 345°)(0.89 ∠ 70°) ] (0.231 ∠ 238°) * = (0.069 – j0.394) + ——————— (1 – 0.694 ∠ 55°) ] Design of amplifiers for optimum noise figure 345 (0.231 ∠ 238°) * = (0.069 – j0.394) + ——————— (0.828 ∠ –43.36°) ] = [(0.069 – j0.394) + (0.055 – j0.274)]* = [0.679 ∠ –79.48°]* ≈ 0.678 ∠ 79.5° 7.5 Design of amplifiers for optimum noise figure Many manufacturers specify optimum driving resistances and operating currents on their data sheets for their transistors to operate with minimum noise figures.2 Designing ampli- fiers for a minimum noise figure then becomes simply a matter of setting the optimum conditions for a particular transistor. In practice, it means that the input network must be made to transform the input source generator impedance (generally 50 Ω) to that of the optimum driving resistance for the transistor to achieve its minimum noise operating After providing the transistor with its optimum source impedance, the next step is to determine the optimum load reflection coefficient needed to properly terminate the tran- sistor’s output. This is given by: s12s21Gs * GL = s22 + ———— 1 – s11Gs ] (7.26) Gs is the source reflection coefficient for minimum noise figure The rest of the design then follows the conventional design methods as you will see in Example 7.10. Example 7.10 The optimum source reflection coefficient (Gs) for a transistor under minimum noise figure operating conditions is Gs = 0.68 ∠ 142°. Its s-parameters under the same condi- tions are: s11 = 0.35 ∠ 165° s12 = 0.035 ∠ 58° s21 = 5.9 ∠ 66° s22 = 0.46 ∠ –31° The d.c parameters for the transistor are Vce = 15 V, Ic = 4 mA, and the operating frequency is 300 MHz. Design a low noise amplifier to operate between a 75 Ω source and a 100 Ω load at 300 MHz. 2 All devices produce electrical noise. In a transistor, noise figure is defined as the ratio of (signal-to-noise ratio at the input) to (signal-to-noise ratio at the output). It follows that if the transistor has a noise figure of 0 dB (power ratio = 1) then the signal-to-noise ratio at both the output and input remains the same and we are said to have a ‘noise free’ transistor. This does not happen in practice although at the time of writing noise figures of 0.5 dB are now being achieved. 346 Microwave amplifiers Given: s11 = 0.35 ∠ 165° s12 = 0.035 ∠ 58° s21 = 5.9 ∠ 66° s22 = 0.46 ∠ –31° ƒ = 300 MHz Vce = 12 V Ic = 4 mA hFE gain = 100 Gs = 0.68 ∠ 142° R L = 100 Ω Required: Low noise amplifier with Zs = 75 Ω, R L = 100 Ω. 1 Using Equation 7.1 Ds = s11s22 – s12s21 = (0.35 ∠ 165°)(0.46 ∠ –31°) – (0.035 ∠ 58°)(5.9 ∠ 66°) = (–0.122 + j0.116) – (–0.115 + j0.171) = (0.056 ∠ –86.25°) 2 Using Equation 7.2, calculate Rollett’s stability factor (K): 1 + |Ds|2 – |s11|2 – |s22|2 K = —————————— 1 + (0.056)2 – (0.35)2 – (0.46)2 = ————————————— = 1.620 The Rollett stability factor (K) calculates to be 1.62 which indicates unconditional stabil- ity. Therefore we may proceed with the design. 3 Input Matching Network The design values of the matching network are shown in Figures 7.10 and 7.12. Here the normalised 75 Ω source resistance is transformed to Gs using two components: Arc AB = shunt C = j1.65 S Arc BC = series L = j0.85 Ω 4 Using Equation 7.12 C1 = ———————— 17.5 pF 2p(300 MHz) (50) 5 Using Equation 7.13 L1 = ——————— ≈ 22.5 nH 2p(300 MHz) Design of amplifiers for optimum noise figure 347 Fig. 7.10 Input matching network for Example 7.10 A = (1.5 + j0) Ω or (0.667 – j0) S, B = (0.21 – j0.52) Ω or (0.667 + j1.653) S, C = (0.212 + j0.33) Ω or (1.433 – j2.184) S 6 Output Matching Network The load reflection coefficient needed to properly terminate the transistor is found from Equation 7.26: s12s21Gs * GL = s22 + ———— 1 – s11Gs ] (0.035 ∠ 58°)(5.9 ∠ 66°) (0.68 ∠ 142°) * = 0.46 ∠ –31° + ———————————————— 1 – (0.35 ∠ 165°)(0.68 ∠ 142°) ] (0.140 ∠ 266°) [ ] = 0.46 ∠ –31° + ———————— 1 – (0.143 – j0.190) = [(0.394 – j0.237) + (–0.045 – j0.152)]* = 0.523 ∠ 48.2° 348 Microwave amplifiers Fig. 7.11 Output matching network for Example 7.10 A = 1.252 + j1.234, B = 2.0 + j1.2, C = 2.0 + j0, D = 0.524 ∠ –48.4° This value along with the normalised load resistance value is plotted in Figure 7.11. The 100 Ω load must be transformed into GL. One possible method is shown in Figure 7.11: Arc AB = shunt L = –j0.72 S Arc BC = series C = –j1.07 Ω Using Equation 7.14, the inductor’s value is L2 = —————————— ≈ 43 nH 2p (300 MHz) (0.62) Using Equation 7.11, the series capacitance is C2 = ——————————— ≈ 8.8 pF 2p (300 MHz) (1.2) (50) The final design including a typical bias network is shown in Figure 7.12. The 0.1 mF capacitors are used only as bypass and coupling elements. The gain of the amplifier can be calculated with Equation 7.15. Design of broadband amplifiers 349 43 nH 8.8 pF 22.5 nH Fig. 7.12 Final circuit for Example 7.10 Using PUFF. Here again, you can use PUFF software to design or verify the amplifier 7.6 Design of broadband amplifiers 7.6.1 Design methods There are many approaches to broadband amplifier design. We can use amplifier mismatching, feedback amplifiers and distributed amplifiers. We show how amplifier mismatching can be used in Example 7.11. 7.6.2 Broadband design using mismatch techniques This method is explained and illustrated by Example 7.11. Example 7.11 A broadband amplifier is to be designed to operate in the 1.5–2.5 GHz frequency range, with a 12 dB transducer power gain, using the HP-Avantek 41410 BJT. The S-parameters of the transistor at the operating range are shown in Table 7.1. Solution. For the purposes of the example we will assume that s12 ≈ 0 and therefore the unilateral case is considered. The expression for the transducer power gain in the unilat- eral case is given as Equation 7.27: Table 7.1 Scattering parameters of HP-AVANTEK BJT f (GHz) s11 s12 s21 s22 1.5 0.6 169° 0.04 58° 5.21 58° 0.41 –40° 2.0 0.6 157° 0.05 55° 3.94 55° 0.41 –45° 2.5 0.61 151° 0.06 55° 3.20 50° 0.4 –49° 350 Microwave amplifiers GTU = GSGOGL (7.27) GTU = gain of amplifier circuit GS = ‘gain’ of source network GO = gain of transistor GL = ‘gain’ of load network 1 – |GS|2 GS = ————— (7.28) |1 – S11GS|2 GO = |S21|2 (7.29) 1 – |GL|2 GL = ————— (7.30) |1 – S22GL|2 Table 7.1 shows that there is a considerable variation of s-parameters with frequency and the degree of variation can be calculated by Equations 7.27 to 7.30. The circuit gain is given by Equation 7.27 and it is dependent on GS, GO and GL. If the individual gains are calculated for a conjugate match at the input and output ports, we will get the results shown in Table 7.2. The maximum gain we can ever hope to achieve over the bandwidth 1.5–2.5 GHz is limited by the minimum gain of the three frequencies, i.e. 12.88 dB at 2.5 GHz. The other two frequencies (1.5 GHz and 2.0 GHz) show gains of 17.07 dB and 14.64 dB respectively but these gains can be reduced to 12.88 dB by mismatching of the ports. Hence, by designing for circuit losses, it is realistic to expect gains of approximately 12 dB over the three frequencies. Inspection of Table 7.2 reveals that little variation of GL occurs with frequency. It is therefore easier to manipulate Gs to achieve the required controlled loss. Table 7.3 shows the gain characteristic required for Gs to achieve an overall average gain of 12 dB over the frequency range. The input circuit should now be designed to produce the required response for Gs shown in Table 7.3. This is carried out by using Table 7.2 Circuit gain vs frequency (when the input and output circuits are conjugately matched) f (GHz) GS,max (dB) GO (dB) GL,max (dB) GTU (dB) 1.5 1.94 14.34 0.79 17.07 2.0 1.94 11.91 0.79 14.64 2.5 2.02 10.1 0.76 12.88 Table 7.3 Expected gains for an average overall gain of 12 dB f (GHz) GS,max (dB) GO (dB) GL,max (dB) GTU (dB) 1.5 – 3.13 14.34 0.79 12 2.0 – 0.7 11.91 0.79 12 2.5 +1.14 10.1 0.76 12 Design of broadband amplifiers 351 Fig. 7.13 Gain of the broadband amplifier constant gain circles for the three frequencies and by choosing a network that will satisfy the response for Gs in Table 7.3. An exact response is not always possible and a compro- mise is often the case. The process of design is one of trial and error and as such is greatly assisted by opti- mising software. As the necessary software is not available with this book, no attempt will be made to do the necessary input broadband matching. Instead we will simply look at the results to see what can be achieved after CAD matching. In Figure 7.13, we show how the gain-frequency response of the amplifier has been improved after optimisation. The amplifier now has a nominal gain of 12 dB è 0.25 dB over the band 1.5–2.5 GHz, instead of the original 4 dB gain fall-off in gain as calculated in Table 7.2. This levelling of gain has been achieved by using a T network as the input matching circuit. This circuit is shown in Figure 7.14. However, the penalty paid for this levelling of gain is poor matching at the input circuit. The return loss of the matching networks of this amplifier is shown in Figure 7.15. Note that the return loss of the input circuit is poor at 1.5 GHz (about 2 dB) but gradually improves towards about 11 dB at 2.5 GHz. The return loss of the output circuit is more even, and ranges from 7.5 dB at 1.5 GHz to about 5 dB at 2.5 GHz. Fig. 7.14 Circuit diagram of the broadband amplifier 352 Microwave amplifiers Fig. 7.15 Return loss of the broadband amplifier 7.7 Feedback amplifiers 7.7.1 Introduction R.F. feedback amplifiers are used in much the same way as feedback elements are intro- duced in operational amplifier circuits to produce constant gain over a desired bandwidth. In this section we shall show you how these amplifiers can be designed. Feedback ampli- fiers are usually designed by first decomposing the combined circuit into individual sub- systems. They are then re-combined into a composite amplifier and its parameters are then calculated to yield the desired results. 7.7.2 Design of feedback amplifiers Consider the basic feedback circuit shown in Figure 7.16. If you look at it closely, you will find that it consists of two basic parts; the feedback circuit which comprises RFB, LFB and its d.c. blocking capacitor CFB situated between points A and B, and the transistor circuit and inductor LD which is also situated between the same two points. Since both circuits are in parallel, we can draw them as shown in Figure 7.17. For this example, we will make considerable use of Y-parameters which were originally introduced in Chapter 6. In Figure 7.17(a), YFB now represents the feedback network, RFB, LFB and its d.c. block- ing capacitor CFB situated between points A and B. Block YA represents the amplifier and the inductor LD. Each network is subject to the same voltage across its terminals; therefore it follows that the currents of each network can be added together to form a composite network YC. This is also shown diagramatically in Figure 7.17(b). From the composite YC Feedback amplifiers 353 Fig. 7.16 A radio frequency feedback amplifier Fig. 7.17 Block diagram of the feedback amplifier of Figure 7.16: (a) composite sections, YA and YFB; (b) combined network, YC network, it is now possible to calculate the circuit gain, input and output admittance as a single circuit in Y-parameters or if you wish you may change them into s-parameters and carry out the calculations using s-parameters. The conversion tables for changing from one type of parameter to another are given in Table 3.1. Hence, the parameters of the circuit can be evaluated using the system above. To clarify the design method, we will show you a very simple example where this tech- nique is used. We will assume that the values for the circuit of Figure 7.18 have already been chosen. Furthermore in order to simplify matters, we will assume that the values are already in Y-parameters and that only resistances are used in the network. The last assump- tion simplifies the mathematics considerably yet it does not obscure the principles which we are trying to use. Example 7.12 In the circuit of Figure 7.18, the open-circuit generator voltage is 200 mV. Calculate (a) the input impedance (Zin), (b) the gain (Av) of the circuit and (c) Vout. You can assume that the d.c. blocking capacitor in the feedback chain has negligible reactance. The transistor Y-parameters for the given frequency of operation are: [ 1/1200 1/40 000 ] Solution. The Y-parameters of the transistor YA are: YA = [ 1/1200 1/40 000 ] [ S = 58 333.3 25 ] 354 Microwave amplifiers Fig. 7.18 Negative feedback amplifier From inspection of the circuit, the Y-parameters of the feedback element YF are: YF = [ 1/10k 1/10k ][ 100 ] mS The composite admittance matrix [YC] = [YA] + [YF]. Hence [YC] = [ 833.3 58 333.3 25] [ mS + [ 933.3 58 233.3 ] We will now obtain the answers. (a) Defining [Dy] as [y11y22 – y12y21] [Dy] = [y11y22 – y12y21] = [9.33 × 1.25 + 1 × 582.3] × 10–8 = 593.96 × 10–8 Using Equation 6.19: y12y21 Dy + y11YL yin = y11 – ———— = ————— y22 + yL y22 + YL y22 + YL [1.25 + 10] × 10–4 Zin = ————— = ———————————— ∆y + y11YL [593.96 + 9.33 × 10] × 10–8 11.25 × 10–4 = —————— = 163.9 W 687.26 × 10–8 R.F. power transistors 355 (b) First find vin: ZinVg 163.69 × 200 vin = ———— = —————— = 15.13 mV Zin + Zg 2163.7 Using Equation 6.18: vout –y21 –582.3 Av = — = —— —— = ———— vin y22 + yL 1.25 + 10 = —— — = –51.76 (c) Output voltage is given by vout = vin × Av = 15.13 × [–51.76] = –783 mV PUFF results. If you wish, you can carry out this example on PUFF by converting the transistor admittance parameters into scattering parameters and generating a transistor device as described in Section 4.9. You can then insert your feedback components and vary them accordingly. 7.7.3 Summary of feedback amplifiers Example 7.12 should now convince you that the procedure used above is useful for evalu- ating feedback amplifiers. However, this method is laborious especially without the use of a computer program. The disadvantage of this method is that each block, YA, YF and YC, is only applicable for one frequency at one time. Thus, if you were designing a broadband circuit, you would have to calculate the parameters for each frequency and then sum up the results. This involves considerable work if hand calculators are used. Another great disadvantage is that the component values that you may have chosen in the first instance may not produce the desired result. Therefore you must carry out the complete procedure again and again until the desired result is achieved. However, it is fortunate that good computer programs, such as ‘SUPERCOMPACT, SPICE, etc.’, provide optimisation facilities and allow you to design the circuit quickly and efficiently. 7.8 R.F. power transistors The design of r.f. power transistors is treated differently from that of the low power linear transistors described in the early part of this chapter. The reason for this is because r.f. power transistors are normally operated in a non-linear mode. This means that manufac- turers tend to only specify output power and output capacitance for a given input power and input capacitance. A typical example is shown in Table 7.4 where values of input 356 Microwave amplifiers Table 7.4 Typical optimum input and conjugate of load impedances for MRF658. Pout= 65 W, Vdc = 12.5 V Frequency (MHz) Zin W Zout W 400 0.620 + j0.28 1.2 + j2.5 440 0.720 + 0j3.1 1.1 + j2.8 470 0.790 + 0j3.3 0.98 + j3.0 490 0.84 + j3.4 0.91 + j3.2 512 0.88 + j3.5 0.84 + j3.3 520 0.90 + j3.6 0.80 + j3.4 impedance and conjugate of load impedances are specified for a given output power and operating d.c. voltage. However, once these values are known, the matching networks are designed in a similar way. You can find a good introduction to the design of power ampli- fiers by consulting Baeten.3 7.9 Summary Many of the commonly used techniques in amplifier design have been covered in this chapter. The circuit topics discussed included transistor stability, maximum available gain and matching techniques. In addition, we produced design examples of conjugate matched amplifiers, conditionally stable transistor amplifiers, optimum noise figure amplifiers, and amplifiers designed for a specific gain. The design techniques of broadband amplifiers, feedback amplifiers and power ampli- fiers were investigated. We also showed how some designs can be carried out using the PUFF software supplied with this book. You should now have a good knowledge of microwave engineering principles that will allow you to do simple amplifier designs and to understand more complicated devices and I would like to remind you of the article ‘Practical Circuit Design’ which has been reproduced on the disk supplied with this book. This article provides many more examples of how PUFF can be used in practical circuit design. There are particularly interesting sections on components, earthing techniques, biasing, passive, active and circuit layout techniques. The article is crowned by the complete design of a 5 GHz microwave ampli- fier from its conception as transistor data to final layout. R.F. design calculations are carried out in Appendix A, input and output line matching and layout using PUFF are shown. Frequency response and gain are checked with PUFF. Bias design for this ampli- fier is also given in Appendix B. Calculations for the design of input and output matching filters are shown in Appendix C. 3 R. Baeten, CAD of a broadband class C 65 watt UHF amplifier, RF Design, March 1993, 132–9. Oscillators and frequency 8.1 Introduction Prior to the invention of an amplifying device (vacuum tube, transistor, special negative- resistance device, etc.) great difficulty was experienced in producing an undamped radio signal. The early radio transmitters used a high frequency a.c. generator to produce a high voltage which was increased by a step-up transformer. The output voltage was applied to a series resonant circuit and the Q of the circuit produced a high enough voltage to jump across a ‘capacitor gap’ to produce a spark1 which in turn produced a radio signal. This principle is still used in a petrol engine today where the spark is used to ignite the petrol mixture. You can frequently hear it on your car radio when the engine cover is removed. Such a radio signal is damped, i.e. it decays exponentially and it produces many harmon- ics which interfere with other communication systems. It is now illegal to transmit a damped oscillation. There are many criteria in choosing an oscillator, but the main ones are: • frequency stability • amplitude stability • low noise • low power consumption • size. Frequency stability is important because it enables narrow-band communication systems to be accurately fixed within a frequency band. An unstable frequency oscilla- tor also behaves like an unstable f.m. modulator and produces unwanted f.m. noise. An amplitude unstable oscillator behaves like an amplitude modulated modulator because it produces unwanted a.m. modulation noise. Even if the oscillation frequency and amplitude can be held precisely, it is inevitable that noise will be produced in an oscil- lator because of transistor noise which includes ‘flicker noise’, ‘shot noise’ and ‘1/frequency’ noise. In other words, oscillator noise is inevitable but it should be kept as low as possible. Low power consumption and small size are specially important in portable equipment. 1 This is the reason why radio operators are often called sparkies. 358 Oscillators and frequency synthesizers 8.1.1 Aim The aims of this chapter are to explain radio frequency oscillators and frequency synthe- sizers. Radio frequency oscillators produce radio frequency signals without an input signal. Frequency synthesizers are used to control and vary the frequency of an oscillator very precisely. 8.1.2 Objectives After reading this chapter, you should be able to: • understand the criteria for oscillation • calculate the criteria (gain and frequency) of • Hartley oscillators • Colpitts oscillators • Clapp oscillators • crystal oscillators • voltage controlled oscillators • phase locked loops • frequency synthesizers 8.2 Sine wave type oscillators An oscillator is a device which produces an output signal without requiring an external input signal. An amplifier can be made into an oscillator if its output signal is fed back into its own input terminals to provide an input signal of the correct amplitude and phase. One easy way of producing an r.f. oscillator is to use an r.f. amplifier and to feed its output signal (with the correct amplitude and phase) back to its input. Figure 8.1 shows a typical common emitter r.f. amplifier. The important things to note about this circuit are its waveforms. Vin is the input sinusoidal applied to the amplifier. Vtc is the inverted voltage appearing across the collector, and Vout is the voltage appearing across the output. The phasor relationship between Vtc and Vout is dependent on the manner in which the secondary winding of T1 is connected. In Figure 8.1, the output winding has been earthed in a manner that will cause Vout to appear with a similar phase to Vin. Fig. 8.1 An r.f. amplifier with associated waveforms Sine wave type oscillators 359 Fig. 8.2 An r.f. oscillator constructed by feeding output to input As Vin and Vout both have similar phases, there is no reason why Vout cannot be connected back to the amplifier input to supply its own input voltage. This is shown schematically in Figure 8.2 where a connection (thick line) has been made between points A and B. Examination of these waveforms shows clearly that if, in addition to the phase requirements, Vout > Vin, then the amplifier will supply its own input and no external signal source will be needed. Therefore the amplifier will produce an output on its own and will become an oscillator! One question still remains unanswered. How do we produce Vout in the first instance without an external Vin? Any operating amplifier produces inherent wideband noise which contains an almost infinite number of frequencies. The collector tuned circuit selects only its resonant frequency for amplification and rejects all other frequencies; therefore only the resonant frequency of the tuned circuit will appear as Vout. Initially, Vout will probably have insufficient amplitude to cause oscillation but as it is fed back around again and again to the amplifier input terminals, Vin will increase in amplitude and, if the circuit has been designed properly, Vin will soon be large enough to cause Example 8.1 The tuned circuit of the oscillator circuit shown in Figure 8.2 has an effective inductance of 630 nH and a total capacitance (CT) of 400 pF. If conditions are set so that oscillations can take place, what is its frequency of oscillation (fosc)? Solution. In Figure 8.2, the frequency of oscillation is determined by the resonant frequency of the tuned circuit. For the values given fosc = = = 10.026 MHz 2π LC 2π 630 nH × 400 pF 8.2.1 Barkhausen criteria The introduction to oscillators above was to provide you with an elementary idea of oscil- lator requirements. To design oscillators, we need a more systematic method. Consider an amplifier with a positive feedback loop (Figure 8.3). 360 Oscillators and frequency synthesizers β Vo Fig. 8.3 An amplifier with positive feedback signal The following terms are defined. Voltage gain (Av) of the amplifier on its own is defined as Av = — (8.1) Voltage gain (Avf) of the amplifier with feedback applied is Avf = — (8.2) By inspection of Figure 8.3 b = output voltage fraction fed back (8.3) v1 = vin + bvo (8.4) vin = v1 – bvo (8.4a) Using Equations 8.2 and 8.4a and dividing each term by v1 vo vo/v1 Avf = ——— = ————— v1 – bvo 1 – bvo/v1 Avf = ——— (8.5) 1 – Avb If b is positive, and if Avb (defined as loop gain) = 1, then the denominator (1–Avb) = 0, or Avb = 1 (8.6) Substituting Equation 8.6 into Equation 8.5 yields Avf = — = ∞ (8.7) Wien bridge oscillator 361 which means that there is an output (vo) in spite of there being no input signal. This system is known as an oscillator. The two main requirements for oscillation are: loop gain amplitude (Avb) = 1 (8.8) loop gain phase = 0° or n360° n is any integer (8.9) Equations 8.8 and 8.9 are known as the Barkhausen criteria for oscillation. Note: Avb = 1 is the minimum condition for oscillation. If Avb > 1, it merely means that the oscillation will start more easily but then, due to non-linearity in the amplifier, Avb will revert back to 1. For ease of understanding the above explanation, I have assumed that there is no phase change in Av and b. In practice, Av is a phasor quantity and if it produces a phase shift of, say, 170°, then b must produce a complementary phase shift of 190° to make the total phase shift of the signal feedback equal to 360° (or any multiple of it). This enables the returned feedback (input) signal to be in the correct phase to aid oscillation. 8.2.2 Summary The Barkhausen criteria state that for an oscillator, the loop gain (Avb) must equal unity and the loop gain phase must be 0° of any integer multiple of 360°. It follows that if the Barkhausen criteria can be met then any amplifier may be made into an oscillator. It is relatively easy to calculate the conditions required for oscillation, but it is important to realise that when oscillation occurs, linear theory no longer applies because the transistor is no longer working in its linear mode. In the discussion that follows, we will show how (i) the conditions for oscillation and (ii) the desired frequency of oscillation may be achieved with various circuits. 8.3 Low frequency sine wave oscillators At frequencies less than about 2 MHz, oscillators are often made using resistances and capacitances as the frequency determining elements instead of LC circuits. This is because at these frequencies, LC elements are physically larger, more expensive, and more difficult to control in production. Two main types of RC oscillators will be previewed. One is the well known Wien bridge oscillator which is used extensively in instruments and the other is the Phase-Shift oscillator. 8.4 Wien bridge oscillator A block diagram of the Wien bridge oscillator is shown in Figure 8.4. The basic parts of this oscillator consist of a non-inverting amplifier2 and an RC network which determines its frequency of operation. 2 This non-inverting amplifier can consist of either two common emitter amplifiers in cascade (one follow- ing the other) or a common base or operational amplifier. 362 Oscillators and frequency synthesizers Fig. 8.4 Wien bridge oscillator 8.4.1 Operation When power is applied to the circuit, currents (including inherent noise currents and volt- ages) appear in the amplifier. This noise voltage is fed back through the Wien (RC network) back to the input of the amplifier. The circuit is designed to allow sufficient feed- back voltage to satisfy the Barkhausen criterion on loop gain (Avb = 1), but only noise frequencies which satisfy the second Barkhausen criterion (∠ Avb = n360°) will cause the oscillation. The circuit will oscillate at a frequency w2 = 1/(R1R2C1C2) radians per second. 8.4.2 Wien bridge oscillator analysis In this analysis, it is assumed that the amplifier does not load the Wien bridge network shown in Figure 8.5. Fig. 8.5 Wien bridge network By inspection Z1 = R1 + 1/(jwC1) 1 1 R2 Z2 = — = ————— = ————— Y2 1/R2 + jwC2 1 + jwC2R2 Wien bridge oscillator 363 vin = ———— (vo) Z1 + Z2 vo Z1 + Z2 — = ——— = 1 + Z1Y2 vin Z2 Substituting for Z1 and Y2 vo (R1 + 1/jwC1)(1 + jwC2R2) — = 1 + ——————————— vin R 2 Multiplying out and sorting the real and imaginary terms vo R1 C2 — — — — = 1 + — + — + j(wC2R1 – 1/(wC1R2)) (8.10) vin R2 C1 For the phase to equal zero, the quadrature or j terms = 0 which gives wC2R1 = 1/(wC1R2) w2 = ———— (8.11) From Equation 8.10, the real part of the equation indicates that the gain of the amplifier (Av) at the oscillation frequency must be |vo| R1 C2 — — Av = — = 1 + — + —— (8.12) |vin| R2 C1 From Figure 8.4, the fraction of the voltage fed-back (b) = |vin|/|vout|. From Equation 8.10 |vin| 1 b = — = ———— — ———— (8.13) |vout| 1 + R1/R2 + C2/C1 For oscillation, the Barkhausen criteria is Avb = 1. Using Equations 8.12 and 8.13 |vo| |vin| Avb = — × — — — |vin| |vo| = (1 + R1/R2 + C2/C1) × ———————— = 1 (1 + R1/R2 + C2/C1) Therefore the Barkhausen gain criteria are satisfied and the circuit will oscillate. 364 Oscillators and frequency synthesizers 8.4.3 Practical Wien bridge oscillator circuits In practical designs and for reasons of economy, variable frequency Wien bridge oscilla- tors use twin-gang3 variable capacitors (C1 = C2 = C) or twin-gang resistors (R1 = R2 = R) to vary the oscillation frequency. For the case where C1 = C2 = C and R1 = R2 = R, Equations 8.11 and 8.12 become w = — rads s–1 — (8.11a) Av = — = 1 + 1 + 1 = 3 (8.12a) Example 8.2 In the Wien bridge oscillator of Figure 8.4, R1 = 100 kΩ, R2 = 10 kΩ, C1 = 10 nF and C2 = 100 nF. Calculate (a) the frequency of oscillation and (b) the minimum gain of the amplifier for oscillation. (a) Using Equation 8.11 w2 = 1/(100 kΩ × 10 kΩ × 10 nF × 100 nF) = 1 000 000 w = 1000 rads–1 fosc = 159.15 Hz (b) Using Equation 8.12, the minimum gain of the amplifier is |vo| R1 C2 — — — =1+— +—— |vin| R2 C1 100 kΩ 100 nF = 1 + —— —— + ———— = 1 + 10 + 10 = 21 10 kΩ 10 nF 8.5 Phase shift oscillators 8.5.1 Introduction The circuit of a phase shift oscillator is shown in Figure 8.6. In this circuit, an inverting amplifier (180° phase shift) is used. To feed the signal back in the correct phase, RC 3 Twin-gang capacitors or resistors are variable elements whose values are changed by the same rotating Phase shift oscillators 365 Fig. 8.6 Phase shift oscillator networks are used to produce an additional nominal 180° phase shift. The theoretical maxi- mum phase shift for one RC section is 90° but this is not easily obtained in practice so three RC stages are used to produce the required phase shift. The transmission (gain or loss) analysis of a three section RC circuit can be difficult unless some simplifying meth- ods are employed. To do this, I shall use matrix methods and assume that you are familiar with matrix addition, subtraction, multiplication and division. 8.5.2 Analysis of the phase shift network In the analysis that follows, it is assumed that the input and output impedances of the tran- sistor are sufficiently large so that they do not load the phase shifting network. It can be shown4 that the two port transmission matrix for a series impedance (Z) is: [ ]1 It can also be shown5 that the two port transmission matrix for a shunt admittance (Y) is: | | V1 V1 A=—— =1 B=—— =Z V2 I2 = 0 I2 V2 = 0 | | I1 I1 C = —— =0‡ D=—— =1 V2 I2 = 0 I2 V2 = 0 ‡ This follows from the diagram since I1 = I2 = 0 | | V1 V1 A=—— =1 B=—— =0‡ V2 I2 = 0 I2 V2 = 0 | | I1 I1 C=—— =Y D=— — =1 V2 I2 = 0 I2 V2 = 0 ‡ This follows from the diagram since V1 = V2 366 Oscillators and frequency synthesizers [ ] The transmission parameters for the six element network shown in Figure 8.7 can be easily obtained by multiplying out the matrices of the individual components. I will simplify the arithmetic by making Z1 = Z2 = Z3 = Z and Y1 = Y2 = Y3 = Y. I have also drawn vo and vin in the conventional manner but the analysis will show that the amplifier gain must be inverted. By inspection of Figure 8.7 Fig. 8.7 Six element network ⎡vo ⎤ ⎡1 Z ⎤ ⎡1 0 ⎤ ⎡1 Z ⎤ ⎡ 1 0 ⎤ ⎡1 Z ⎤ ⎡ 1 0 ⎤ ⎡vin ⎤ ⎢ I ⎥ = ⎢0 1 ⎥ ⎢Y 1 ⎥ ⎢0 1 ⎥ ⎢Y 1 ⎥ ⎢0 1 ⎥ ⎢Y 1 ⎥ ⎢ I2 ⎥ ⎣ 1⎦ ⎣ ⎦ ⎣ ⎦⎣ ⎦⎣ ⎦⎣ ⎦⎣ ⎦⎣ ⎦ ⎡vo ⎤ ⎡1 + YZ Z ⎤ ⎡1 + YZ Z ⎤ ⎡1 + YZ Z ⎤ ⎡vin ⎤ ⎢I ⎥ = ⎢ Y 1⎥ ⎢ Y 1⎥ ⎢ Y 1 ⎥ ⎢ I2 ⎥ ⎣ 1⎦ ⎣ ⎦⎣ ⎦⎣ ⎦⎣ ⎦ ⎡vo ⎤ ⎡1 + YZ Z ⎤ ⎡1 + 3YZ + Y 2 Z 2 YZ 2 + 2 Z ⎤ ⎡vin ⎤ ⎢I ⎥ = ⎢ Y ⎢ 1 ⎥ ⎣ Y 2 Z + 2Y ⎥ ⎢I ⎥ ⎣ 1⎦ ⎣ ⎦⎢ YZ + 1 ⎦ ⎥ ⎣ 2⎦ ⎡vo ⎤ ⎡Y 3 Z 3 + 5Y 2 Z 2 + 6YZ + 1 Y 2 Z 3 + 4YZ 2 + 3Z ⎤ ⎡vin ⎤ ⎢I ⎥ = ⎢ 3 2 2 ⎥ ⎢I ⎥ ⎣ 1 ⎦ ⎣ Y Z + 4Y Z + 3Y ⎢ Y 2 Z 2 + 3YZ + 1 ⎦⎥ ⎣ 2⎦ Since we have assumed that the transistor impedance does not load the circuit, I2 = 0. = A = Y 3 Z 3 + 5Y 2 Z 2 + 6YZ + 1 vin I2 = 0 Substituting for Y and Z vo 1 5 6 = + + +1 (8.16) vin I2 = 0 ( jωCR) 3 ( jωCR) 2 ( jωCR) Sorting out real and imaginary terms vo 1 5 6 = + + +1 vin I2 = 0 ( jωCR) 3 ( jωCR) 2 ( jωCR) Phase shift oscillators 367 ⎡ 5 ⎤ ⎡ 1 6 ⎤ = ⎢1 − 2⎥ + j⎢ − 3 ωCR ⎥ (18.6a) ⎣ (ωCR) ⎦ ⎣ (ωCR) ⎦ [real part] [imaginary part] The Barkhausen criterion for oscillation is that the voltage through the network must undergo a phase change of 180°, i.e. imaginary or quadrature terms are zero. –6 1 —— + ——— = 0 ωCR (ωCR)3 6 = ——— and w2 = ——— (8.17) (wCR)2 6(CR)2 The real part of Equation 8.16a at resonance is: vo –5 — = ——— + 1 (8.18) vin (wCR)2 and using Equation 8.17 to substitute for 1/(wCR)2 — = –5 × 6 + 1 = –29 = 29 ∠ 180° Since vo/vin = Av Av = 29 ∠ 180° (8.19) —— = 29 (8.19a) From Figure 8.6, the fraction of the voltage fed back b = |vin|/|vo|. Using Equation 8.19 |vin| 1 b = —— = —— (8.20) |vo| 29 To check for oscillation at resonance, the Barkhausen criterion is Avb = 1. Using Equations 8.19a and 8.20 |vo| |vin| 1 Avb = —— × —— = 29 × ——= 1 |vin| |vo| 29 Therefore the Barkhausen criteria are met and the circuit will oscillate. 368 Oscillators and frequency synthesizers 8.6 Radio frequency (LC) oscillators 8.6.1 Introduction Oscillators operating at frequencies greater than 500 kHz tend to use inductors and capac- itors as their frequency controlling elements because: • RC values are beginning to get inconveniently small; • LC values are beginning to assume practical and economical values. 8.6.2 General analysis of (LC) oscillators In the analysis of the oscillators within this section, it must be realised that all calculations to establish the conditions and frequency of oscillation are based on linear theory. When oscillation occurs, the transistor no longer operates in a linear mode and some modifica- tion (particularly bias) is inevitable. The simplified solutions derived for each type of oscillator are based on the following • The input impedance of the transistor does not load the feedback circuit. • The output impedance of the transistor does not load the feedback circuit. • The collector–emitter voltage (VCE) is the output voltage. • The emitter–base voltage (VEB) is the input voltage. • The feedback circuit is purely reactive (no resistive losses). • If the transistor is operated in the common emitter configuration, a positive base input voltage will result in an inverted collector voltage. If the transistor is operated in the common base configuration, there is zero phase shift through the transistor. • There is 0 or 2p radians (360°) shift through the loop gain circuit. In the case of a common emitter amplifier, if p radians (180°) shift is caused by the transistor when its collector load is resistive and/or resonant, then a further p radians shift will be required in the feedback circuit to return the feedback signal in the correct phase. With a common-base amplifier, if 0 radians phase shift is produced by the transistor, then zero phase shift through the feedback network is required to return the feedback signal in the correct phase. • For clarity, oscillator outputs are not shown in Figures 8.8, 8.9 and 8.10. Outputs are taken from either the collector or emitter via capacitance coupling or magnetic coupling from the inductor. The above assumptions are approximately true in practice and form a reasonably accurate starting point for oscillator design. 8.7 Colpitts oscillator A schematic diagram of the Colpitts oscillator circuit is shown in Figure 8.8. Two capaci- tors, C1 and C2, are connected in series to provide a divider network for the voltage devel- oped across points C and B. The tuned circuit is formed by the series equivalent capacitance of C1 and C2 and the inductor L. Colpitts oscillator 369 Fig. 8.8 Colpitts oscillator The transistor is operated in the common base configuration. The base is a.c. earthed via C4. The point B is a.c. earthed through capacitor C3. If the voltage at point C is posi- tive with respect to earth, then point E is also positive with respect to earth. Hence the tran- sistor supplies its own input voltage in the correct phase. 8.7.1 Frequency of oscillation Using the assumptions of Section 8.6.2 and since we assume that there is no loading of the tuned circuit at resonance, XL = XC, yielding —— + —— = wL ωC1 wC2 w2(L) = — + — — — C1 C2 w2 = — L [ — — +— C2 ] (8.21) 8.7.2 Conditions for oscillation From Figure 8.8 and using the assumptions of Section 8.6.2 VEB = vin and VCB = vo By inspection of Figure 8.8 vin = ————— vo (8.22) Xc1 + Xc2 370 Oscillators and frequency synthesizers By definition, b = vin/vo, therefore b = ———— (8.23) Xc1 + Xc2 By definition, Av = vo/vin and using Equation 8.22 Xc1 + Xc2 C2 C2 Av = ———— = — + 1 or 1+—— (8.24) Xc2 C1 C1 For oscillation, we must satisfy the Barkhausen criteria and ensure that the loop gain Avb = 1. Using Equations 8.23 and 8.24 Xc1 + Xc2 Xc2 Avb = ———— × ———— = 1 Xc2 Xc1 + Xc2 Therefore the circuit will oscillate provided [ ]C2 Av ≥ 1 + —— (8.25) Summing up Equation 8.21 determines the frequency of oscillation and Equation 8.25 determines the minimum gain of the amplifier for oscillation. Example 8.3 If in Figure 8.8 C1 = 10 pF and C2 = 100 pF and the desired oscillation frequency is 100 MHz, calculate (a) the value of the inductor and (b) the minimum voltage gain of the amplifier. Assume that the transistor does not load the tuned circuit. (a) From Equation 8.21 L [ w2 = — — + — C1 C2 Transposing and substituting for C1 and C2 [ ] L = ——————— —— + ——— H — (2p × 100 MHz)2 10 pF 100 pF 11 × 1012 F = ————— ————— 3.948 × 1017 [ 100 ] H = 278.6 nH (b) From Equation 8.24 the minimum voltage gain of the amplifier is C2 100 pF — = 1 + ——— = 11 C1 10 pF Hartley oscillator 371 8.8 Hartley oscillator A schematic diagram of the Hartley oscillator circuit is shown in Figure 8.9. Note that the Hartley circuit is the dual of the Colpitts circuit where inductors and capacitors have been interchanged. Inductor L in conjunction with capacitor C forms the tuned circuit. Inductor L also serves as an auto-transformer. In an auto-transformer, the voltage developed6 across points E and B is proportional to the number of turns (n2) between E and B. Similarly, the voltage developed across points C and B is proportional to the number of turns (n1 + n2) between points C and B. Fig. 8.9 Hartley oscillator The transistor is operated in the common base configuration. The base is a.c. earthed via capacitor C4. The point B is a.c. earthed through capacitor C3. C2 is a d.c. blocking capaci- tor. If the voltage at point C is positive with respect to earth, then point E is also positive with respect to earth. Hence the transistor supplies its own input voltage in the correct phase. 8.8.1 Frequency of oscillation Using the assumptions of Section 8.6.2 and since we assume that there is no loading of the tuned circuit at resonance, XL = XC, yielding wL = —— w2 = —— (8.26) 8.8.2 Conditions for oscillation From Figure 8.9 and using the assumptions of Section 8.6.2 VEB = vin and VCB = vo 6 This assumes that the same flux embraces both parts of the auto-transformer. 372 Oscillators and frequency synthesizers From Figure 8.9, since inductor L serves as an auto-transformer vin = ——— vo (8.27) n1 + n2 By definition, b = vin/vo. Therefore b = ——— (8.28) n1 + n2 By definition, Av = vo/vin and using Equation 8.27 n1 + n2 n1 n1 Av = —— — —— = — + 1 or 1+—— (8.29) n2 n2 n2 For oscillation, we must satisfy the Barkhausen criteria and ensure that the loop gain Av b = 1. Using Equations 8.28 and 8.29 n1 + n2 n2 Avb = ——— × ——— = 1 n2 n1 + n2 Therefore the circuit will oscillate provided [ ]n1 Av ≥ 1 + — — (8.30) Summing up Equation 8.26 determines the frequency of oscillation and Equation 8.30 determines the minimum gain of the amplifier. 8.9 Clapp oscillator A schematic diagram of the Clapp oscillator circuit is shown in Figure 8.10. Two capaci- tors, C1 and C2, are connected in series to provide a divider network for the voltage devel- oped across points C and B. The tuned circuit is formed by the equivalent series capacitance of C1, C2 and CT and the inductor L. The Clapp oscillator is a later develop- ment of the Colpitts oscillator except that an additional capacitance CT has been added to improve frequency stability and facilitate design. The transistor is operated in the common base configuration. An r.f. choke is used to feed d.c. power to the collector. The reactance of the r.f. choke is made deliberately high so that it does not shunt the tuned circuit. The base is a.c. earthed via capacitor C3. The point B is earthed directly. If the voltage at point C is positive with respect to earth, then point E is also positive with respect to earth. Hence the transistor supplies its own input voltage in the correct phase. 8.9.1 Frequency of oscillation Using the assumptions of Section 8.6.2 and since we assume that there is no loading of the tuned circuit at resonance, XL = XC, yielding Clapp oscillator 373 Fig. 8.10 Clapp oscillator wL = — + — + — — — — wC1 wC2 wCT w2L = — + — + — — — — C1 C2 CT [ ] CT CT w2 = —— 1 + — + —— — (8.31) LCT C1 C2 If [CT/C1 + CT/C2] << 1, then Equation 8.31 becomes w2 = —— (8.31a) Equation 8.31a is the preferred mode of operation for the Clapp oscillator for the follow- ing reasons. • It allows CT and L to be the main contributors for determining the oscillation frequency. This is particularly useful when the oscillation is to be set to another frequency because only one control is needed. In many cases, CT is a varactor (capac- itance diode) whose capacitance can be changed electronically by applying a d.c. control voltage. This is particularly usefully in crystal oscillators which we shall be describing shortly. • It provides freedom for setting C1 and C2 to get the required values for easy oscillation. C1 and C2 can be made reasonably large provided their ratio remains the same. • Larger values of C1 and C2 help to swamp transistor inter-electrode capacitances which change with operating bias and temperature. 374 Oscillators and frequency synthesizers 8.9.2 Conditions for oscillation From Figure 8.10 and using the assumptions of Section 8.6.2 VEB = vin and VCB = vo By inspection of Figure 8.10 vin = ————— vo (8.32) Xc1 + Xc2 By definition, b = vin/vo. Therefore b = ————— (8.33) Xc1 + Xc2 By definition, Av = vo/vin and using Equation 8.32 Xc1 + Xc2 C2 C2 Av = ———— = —— + 1 or 1 + —— (8.34) Xc2 C1 C1 For oscillation, we must satisfy the Barkhausen criteria and ensure that the loop gain Avb = 1. Using Equations 8.33 and 8.34 Xc1 + Xc2 Xc2 Avb = ———— × ———— = 1 Xc2 Xc1 + Xc2 Therefore the circuit will oscillate provided [ ]C2 Av ≥ 1 + —— (8.35) Summing up Equation 8.31 determines the frequency of oscillation and Equation 8.35 determines the minimum gain of the amplifier for oscillation. Example 8.4 Calculate the approximate frequency of oscillation for the Clapp oscillator circuit of Figure 8.10 when CT = 15 pF, C1 = 47 pF, C2 = 100 pF and L = 300 nH. Solution. Using Equation 8.31 [ ] [ ] CT CT 1 15 15 w2 = —— 1 + — + — = ———— — — — ———— 1 + — + —— LCT C1 C2 300 nH × 15 pF 47 100 = 2.222 × 1017 × 1.469 = 3.264 × 1017 w = 571 314 274.3 radians/s Voltage-controlled oscillator 375 fosc = 90.93 MHz An alternative approach is to calculate the combined series capacitance of the circuit: Ctotal = [1/15 pF + 1/47 pF + 1/100 pF]–1 = 10.21 pF fosc = = 90.93 MHz 300 nH × 10.21 pF 8.10 Voltage-controlled oscillator A voltage-controlled oscillator is shown in Figure 8.11(a). If you examine this circuit, you will find that it is almost identical to that of the Clapp oscillator (Figure 8.10). The exception is that CT has been replaced by CV which is a variable capacitance diode or varactor. The voltage across the varactor and hence its capacitance is controlled by varying the varactor voltage. C3 is a d.c. blocking capacitor used to isolate the varactor voltage from the collector voltage. All the conditions relating to the Clapp oscillator apply here except that CT in all the equations must be replaced by Cv. 8.10.1 Frequency of oscillation The frequency of oscillation is that calculated by Equation 8.31 except that CT must be replaced by Cv. 8.10.2 Oscillator gain If you plotted the frequency of oscillation against the varactor voltage, you would get a curve similar to that of Figure 8.11(b). The frequency sensitivity or frequency gain of the oscillator is defined as (a) (b) Fig. 8.11 (a) Voltage-controlled oscillator; (b) oscillator frequency (fr) vs varactor (Vr) 376 Oscillators and frequency synthesizers ko = —— (8.36) Equation 8.36 is important because it tells us what voltage must be applied to the varactor to alter the oscillator frequency. In this case, the sensitivity is positive because the slope Dƒ/Dv is positive. However, if the varactor in Figure 8.11(a) is connected in the opposite direction then a negative voltage would be needed for control and, in this case, the sensitivity slope will be negative. We will be returning to the question of frequency sensitivity when we discuss phase locked loops. Summing up Equation 8.31 determines the frequency of oscillation when you substi- tute Cv for CT. Equation 8.35 determines the minimum gain of the amplifier for oscilla- tion. Equation 8.36 describes the frequency sensitivity or frequency gain of the oscillator. 8.11 Comparison of the Hartley, Colpitts, Clapp and voltage-controlled oscillators • The Hartley oscillator is very popular and is used extensively in low powered oscillators where the inductor value can be increased by winding the coil on ferrite cored material. It is used extensively as the local oscillator in domestic superhet radio receivers. • The Colpitts oscillator is used in cases where a piezo-electric crystal is used in place of the inductor. • The Clapp oscillator finds favour in electronically controlled circuits. It is more frequency stable than the other two oscillators and can be easily adapted for crystal control oscillators. • The voltage-controlled oscillator is ideal for varying the frequency of an oscillator elec- tronically. This is particularly true in phase locked loops and frequency synthesizers which will be explained shortly. 8.12 Crystal control oscillators 8.12.1 Crystals Crystals are electromechanical circuits made from thin plates of quartz crystal or lead–zirconate–titanate. They are sometimes used in place of LCR-tuned circuits. The electrical symbol for a crystal7 and its equivalent circuit are shown in Figure 8.12. In this circuit, the capacitance between the connecting plates is represented by Co, while L and C represent the electrical effect of the vibrating plate’s mass stiffness, and R repre- sents the effect of damping. The circuit has two main resonant modes; one when L, C and R are in series resonance and the other at a frequency slightly above the series resonant frequency when the total series combination is inductive and resonates with Co to form a parallel resonant circuit. Engineers can use either of these resonant modes in their designs. 7 It is common practice to abbreviate the term crystal resonator to xtal. Crystal control oscillators 377 Fig. 8.12 Electrical equivalent circuit of a crystal resonator Quartz and lead–zirconate–titanate are piezo-electric, i.e. they vibrate mechanically when an electrical signal is applied to them and vice-versa. The resonant frequencies at which they vibrate are dictated by their geometrical sizes, mainly plate thickness and angle of crystal cut with respect to the main electrical axes of the crystal. Crystals are normally cut to give the correct frequency in a specified oscillator circuit at a given temperature, nominally 15°C. Plate thickness reduces with frequency and at the higher frequencies, plate thickness becomes so thin that the crystal is fragile. To avoid this condition and still operate at frequencies up to 200 MHz, manufacturers often resort to overtone operation where they cut the crystal to a lower frequency but mount it in such a manner that it operates at a higher harmonic. Overtone crystals which operate at third, fifth and seventh overtones are The angle of cut determines the temperature stability of the crystal. Typical types of cuts are the AT cut, BT cut and SC cut. The frequency stabilities of these cuts against temperature are shown in Figure 8.13. The AT cut is popular because it is reasonably easy and cheap to make. It has a positive temperature coefficient (frequency increases) when the ambient temperature changes outside its design (turnover) temperature. The BT cut crys- tal has a negative temperature coefficient when the temperature is outside its turnover Fig. 8.13 Frequency stability against temperature 378 Oscillators and frequency synthesizers temperature. The SC cut crystal has an almost zero temperature coefficient but this crystal is difficult to make because it is first cut at an angle with respect to one axis and then rotated and cut again at a second angle to another axis. From Figure 8.13, you should also note that changes of frequency for the crystal itself against temperature are very small. To put the matter in perspective, 1 part in 108 is equivalent to about 1 Hz in 100 MHz, but remember in a practical circuit, there are other parts (transistors, external capacitors, etc.) which will affect frequency as Crystal resonators manifest very high Qs and values of Qs greater than 100 000 are common in 10 MHz crystals. Metallic plates are used to make electrical connections to the piezo material and the whole assembly is usually enclosed in a hermetically sealed can or glass bulb to minimise oxidation and the ingress of contaminants. 8.12.2 Crystal controlled oscillator circuits Crystal oscillators are particularly useful because of their frequency stability and low noise properties. Figure 8.14 shows how a crystal is used in its parallel mode as an induc- tor in a Colpitts oscillator circuit. When used in this manner, it is sometimes called a Pierce oscillator. Such a circuit has the advantage of quick frequency changes by simply switching in different crystals. The resonance frequency of oscillation is determined by the equivalent circuit capacitance across the crystal and the equivalent inductance of the crystal. To order such a crystal from the manufacturer, it is essential to tell the manufac- turer the model of the crystal required, its mode of operation (series or parallel), operat- ing frequency and parallel capacitance loading. Typical capacitance loads are 10 pF, 30 pF and/or 50 pF. Figure 8.15 shows how a crystal is used in its series resonance mode as an inductor in a Clapp type oscillator. Crystal oscillators are used because they offer vastly superior frequency stability when compared with LC circuits. As crystal Qs are very high, crystal oscillators tend to produce much less noise than LC types. Typical values of stabilities and frequency ranges offered Fig. 8.14 Colpitts xtal oscillator Crystal control oscillators 379 Fig. 8.15 Clapp xtal oscillator by crystal oscillators are given in Table 8.1. Explanatory terms for some abbreviations are given below the table. Cathodeon and OSA are company names. Table 8.1 Oscillator type VCO OCXO TCXO TCXO (analogue) (digital) Type no Cathodeon FS 5909 Cathodeon FS 5951 Cathodeon FS 5805 OSA DTCXO 8500 Frequency range 5–20 MHz 300kHz–40 MHz 5–15 MHz 1–20 MHz Output TTL TTL TTL or sine Sine Temperature range –25 to 80˚C 0–60˚C è0.1 ppm or –10 to 55˚C –40 to 85˚C (°C) and stability è50 ppm on set –40 to 70˚C è1 ppm or –20 0.5 ppm or –20 to frequency ±0.2 ppm to 70˚C ±2 ppm 70˚C ±0.3 ppm Frequency adjust External volt Internal trimmer External resistor External resistor (50 ppm) Ageing rate 2 ppm/year 3 × 10–9 ppm day 1 ppm/year <1 ppm/year Oscillator supply 5–15 V 5V 9V 12 V Oven supply 9–24 V Power oscillator 20 mA at 12 V 40/60 mA 9 mA <200 mW Power oven 3–8 W Package size (mm) 36.1 × 26.7 × 15 36.1 × 26.8 × 25.4 36.1 × 26.8 × 19.2 35.33 × 26.9 × 7.19 VCO = voltage-controlled oscillator usually like that of Figure 8.11(a). OCXO = oven-controlled crystal oscillator. This type of oscillator is usually mounted in an oven operating at 75°C. The frequency stability is extremely good because, as you can see from Figure 8.13, the frequency of a crystal is very stable. The disadvantages are additional bulk, size, weight and oven consumption of additional electrical power. The last is particularly undesirable in battery operated equipment. TCXO (analogue) = temperature-compensated crystal oscillator which uses compensating circuits (usually ther- mistors) to correct frequency drifts with temperature. TCXO (digital) = temperature-compensating oscillator which uses a microprocessor or look-up tables to correct frequency drifts with temperature. 8.12.3 Summary for crystal oscillators In Section 8.12 you have gained an insight into quartz crystals and their properties. You have also seen how crystals are used in crystal oscillators, how they operate, their frequency stability with temperature, and factors which affect the ordering of crystals for use in oscillators. 380 Oscillators and frequency synthesizers 8.13 Phase lock loops 8.13.1 Introduction The necessity for stable, low noise, power oscillators at very high frequencies has led to many innovative oscillator design systems. Consider the case where a stable, low noise 3.6 GHz oscillator is required for a transmitter. Ideally we would like to use a crystal oscilla- tor operating at 3.6 GHz. However, this is not possible because the maximum operating range for a crystal oscillator is about 300 MHz. Fig. 8.16 Producing a crystal controlled high frequency signal One way of producing the 3.6 GHz signal would be to use the scheme shown in Figure 8.16 where a 300 MHz oscillator is fed into a cascade of frequency multipliers8 which amplify and select various harmonics of 300 MHz signal to produce the final 3.6 GHz. This method is expensive, requires a lot of circuit adjustment and is relatively inefficient. However, it can be used and is still in use particularly at frequencies which cannot be easily amplified. The great disadvantage of this method is that frequency multiplication increases unwanted f.m. noise and the oscillator output is generally noisy. Another method of producing this signal would be to use a voltage-controlled LC oscil- lator at 3.6 GHz, divide its frequency, and compare its divided frequency against a refer- ence crystal oscillator through a frequency or phase comparator which then emits a controlling voltage to shift the frequency back to the desired frequency. Such an arrange- ment is shown in Figure 8.17. This system is the basis of phase locked loop systems which we will now discuss more extensively. Fig. 8.17 A simple phase lock oscillator system 8 A frequency multiplier can be made by over-driving an amplifier with a large signal so that the amplifer limits and produces a quasi-square waveform output. Fourier analysis tells us that a square waveform consists of many harmonics and we can select the desired harmonic to give the required signal. Phase lock loops 381 8.13.2 Elements of a phase locked loop system The block diagram of the basic phase locked loop (PLL) is shown in Figure 8.18. The phase detector, or phase comparator, compares the phase of the output waveform from the voltage-controlled oscillator with the phase of the r.f. reference oscillator. Their phase difference causes an output voltage from the phase detector, and this output voltage is fed to a low pass filter which removes frequency components at and above the frequencies of the r.f. input and the VCO. The filter output is a low frequency voltage which controls the frequency of the VCO. Fig. 8.18 The basic phase locked loop When the loop is ‘in lock’, the phase difference has a steady value, which causes a d.c. voltage output from the filter. This d.c. voltage is sufficient to cause the VCO output frequency to become exactly equal to the input frequency. The two frequencies must be synchronised, otherwise there will be a continually-changing phase difference, the VCO input voltage will not be steady, and the loop will not be locked. Thus the loop ‘locks onto’ the reference frequency. Once the loop has locked, the reference frequency may vary, and the VCO output will follow it, over a range of frequencies called the hold-in range. That is the PLL will stay in lock, providing the output frequency does not fall outside the hold-in range. In the following sections, we will look at each of the components of the PLL in turn, followed by the closed loop frequency response and step response. 8.13.3 The phase detector The basic principle behind phase detection is signal multiplication. Figure 8.19 shows the principle using an ideal analogue multiplier. The VCO output voltage is represented by vv = sin wvt where wv is its angular frequency. The reference input signal is an unmodulated carrier vr sin (wrt + f) where wr is the input angular frequency and f is its relative phase to vv at t = 0. The multiplier output is vr vv = sin (wrt + f) sin wvt (8.37) A little trigonometry9 shows that vr vv = sin (wrt + f) sin wvt = 0.5 {cos[(wr – wv)t + f] – cos (wr + wv)t + f} 9 cos (A – B) = cos A cos B + sin A sin B and cos (A+B) = cos A cos B – sin A sin B and subtracting the two equations yields cos (A – B) – cos (A + B) = 2 sin A sin B or sin A sin B = 0.5 [cos (A – B) – cos (A + B)] 382 Oscillators and frequency synthesizers Fig. 8.19 Multiplication of two sine waves The low pass filter removes the sum frequency (wr + wv) and the oscillator frequencies, leaving the difference–frequency component: vf = 0.5{cos[(wr – wv)t + f]} (8.38) When the loop is in lock, the VCO frequency becomes equal to the reference input frequency and wr = wv and Equation 8.38 becomes vf = 0.5[cos f] when locked (8.39) This is a d.c. level proportional to the cosine of the phase difference (f) between the two signals at the input of the phase detector. Figure 8.20 shows the variation of this voltage with phase difference. The sensitivity of Figure 8.20 is defined as rate of filter d.c./phase difference. It is maxi- mum at points A and B when the phase difference between the two signals is è90° and minimum at point C where the phase difference is zero. It follows that if we want maxi- mum sensitivity, then the reference oscillator and the VCO should be out of phase by 90°. For the sake of clarity, let us choose point A. For this point we see: • filtered d.c. output is zero for f = –90° • filtered d.c. output is positive for –90° < f < 0° • filtered d.c. output is negative for –180° < f < –90° Fig. 8.20 Phase detector output when locked Phase lock loops 383 Assume that the reference input frequency is constant. When the VCO drifts so that the relative phase shift –90° < φ < 0°, a positive voltage will be generated for its frequency correction. When the VCO drifts in the opposite direction so the phase shift is –180° < φ < –90°, a negative voltage will be generated for frequency correction. If the VCO is designed for the right sense of correction, it follows that the filter d.c. output voltage will keep the phase and hence the frequency constant. 8.13.4 Types of phase detectors In practice, analogue multipliers are seldom used as phase detectors, because there are simpler circuits which can achieve the same overall result cheaper and faster. However, the theory of the analogue multiplier applies to these circuits too. We will now examine two basic phase detectors: the analogue switch, and the digital type. Analogue switch type One typical analogue switch phase detector is shown in Figure 8.21. In this circuit, the principle of operation described earlier is carried out by multiplying the two signals as described earlier. Vr remains the reference input signal, but part of the VCO signal is used to produce a square wave which switches the diodes ON and OFF when the square wave- form is 1 and 0 respectively. Since a square wave is composed of a series of sine waves, it is apparent that the multiplication process is obtained and if a low pass filter is used after vo, we will get the required d.c. term for VCO control as before. Fig. 8.21 Analogue type phase detector Digital phase detectors Digital phase detectors have both inputs in the form of digital waveforms. Typically, they use digital logic circuitry, such as TTL or CMOS. The AND gate type The most obvious digital equivalent of the analogue multiplier is an AND gate, as shown in Figure 8.22(a). For the AND gate, with logical inputs A and B, the output is given by Y = A.B. So, when the two input square waves have the same frequency and are in phase, the average output voltage is maximum and equal to half the logic 1 output voltage (Vo). 384 Oscillators and frequency synthesizers Fig. 8.22 The AND gate digital phase detector: (a) AND gate phase detector; (b) input and output waveforms for different phase shifts; (c) filter d.c. output versus phase difference, with locked loop Figure 8.22(b) shows input square waves with various amounts of phase shift and corre- sponding output waveforms. Figure 8.22(c) shows that, with input signals of the same frequency, the average output voltage varies linearly with the phase (f). The filter output10 voltage (vd), when the loop is locked, is vd = (V1/2)(1 + f/p) for –p < f < 0 (see slope side A) vd = (V1/2)(1 – f/p) for 0 < f < p (see slope side B) 10 The filter output voltage (v ) is defined as the output voltage from the detector after removal of the oscilla- tor and sum frequencies. Phase lock loops 385 This function, which peaks at f = 0, is analogous to the cosine function of the analogue multiplier, which also peaks at f = 0. Note: Although an AND gate has been featured in this case, you should be aware that it is also possible to use a NAND gate or an exclusive-OR gate as a phase detector but expect phase inversion in the output signal. Gain sensitivity of the AND gate The gain sensitivity or gain (kf) of a phase detector is defined as output voltage change (vd)/phase difference (qe) change or kf = —— (8.40) Using the same definition for Figure 8.22 we obtain for an AND gate kf = ——— (8.40a) The sign of kf is dependent on the point used for the definition. If you use point A in Figure 8.22(c), you will get a positive slope and hence a positive value for kf whereas point B will give a negative slope and a negative value for kf. The flip-flop type phase detector In some applications of the phase locked loop, one or the other of the digital inputs to the phase detector may not be a square wave. For instance one input may come from the output of a counter used as a frequency divider, whose output waveform has a mark:space ratio which changes when the division factor is changed. Such a waveform is not suitable for use with the AND gate or the EX-OR gate. An alternative, which avoids this disad- vantage, is the flip-flop. This is shown in Figure 8.23(a). Here, rising edges of one input set the output (Q) to logical 1, and rising edges of the other input reset the output (Q) to logical 0, as shown in the waveforms of Figure 8.23(b). You should see that the average output vd varies with f as in Figure 8.23(c) and not with the mark: space ratios of the input Gain sensitivity of the flip-flop detector The gain sensitivity or gain (kf) of Figure 8.23 is defined as kf = — (8.41) The sign of kf is dependent on the point used for the definition. If you use slope B in Figure 8.23(c), you will get a positive slope and hence a positive value for kf whereas point A will give a negative slope and a negative value for kf. 386 Oscillators and frequency synthesizers Fig. 8.23 A set–reset (SR) flip-flop used as a phase detector, with triggering on the rising edges of the input wave- form: (a) set–reset flip-flop; (b) input and output waveforms; (c) average output voltage versus phase difference 8.13.5 The filter The purpose of the filter is to remove the two oscillator frequencies ƒr and ƒVCO and the sum frequencies so that they do not cause instabilities in the loop system. The low pass filter is a simple RC network. In many applications it is a simple first-order single lag filter comprising just a series resistor followed by a shunt capacitor. In some cases a lower frequency single lag filter is used for loop compensation. In other cases a slightly more complicated lag-lead RC network is used. Loop compensation is discussed further in the section on closed-loop response. 8.13.6 The d.c. amplifier In many cases, the output from the phase detector is not sufficient to control the voltage- control led oscillator (VCO); therefore some form of d.c. amplification is necessary. Figure 8.24 shows three voltage gain amplifiers and their gain (volts out/volts in) parameters kA = vo/vi. Phase lock loops 387 Fig. 8.24 (a) Common emitter; (b) inverting op-amp; (c) non-inverting op-amp For Figure 8.24(a) kA ≈ –Rc/Re (8.42) For Figure 8.24(b) kA ≈ –Rf/R1 (8.43) For Figure 8.24(c) kA ≈ (Rf + R1)/R1 (8.44) The bandwidth of the d.c. amplifier must be very high when compared to the loop band- width (explained later) otherwise loop instability will occur. 8.13.7 The voltage-controlled oscillator (VCO) The sine wave VCO described in Section 8.10 is a suitable oscillator for use in phase locked loops, but other types such as the digital type oscillator shown in Figure 8.25 can also be used. The sine wave type is used as the oscillator in r.f. transmitters, and as local oscillators in radio and television receivers and as synthesised oscillators in mobile phones and signal generators. In these applications a pure sine wave is the ideal. With varactor diode type oscillators, the relation between the oscillator frequency and the control volt- age is chiefly dependent on the chosen varactor and its direction of connection. Most varactors vary their capacitance as Va where a can range from 0.5 to 3. Fig. 8.25 Digital free-running multi-vibrator with voltage-controlled frequency 388 Oscillators and frequency synthesizers The linear, square wave type of VCO is suitable for use in a PLL system used for frequency demodulation. This is done at the receiver intermediate frequency, so no great strain is made on the operating frequency of the digital circuitry. If the loop is in lock, then the VCO frequency must be following the input frequency. In this case the VCO’s control voltage, which is also the demodulated output from the loop, is linearly related to the frequency shift and, hence, to the original frequency modulation. Gain sensitivity of a VCO The gain sensitivity of a VCO is defined as ko = dƒ/dvc (8.45) dƒ is the change in VCO frequency dvc is the change in control voltage vc Frequency of a VCO If we define ƒFR as the free-running frequency of a VCO when there is zero correction volt- age from the phase detector, and assume oscillator control linearity, then by using Equation 8.45 we can describe the frequency (ƒ) of the VCO as ƒ = ƒFR + Dƒ = ƒFR + kovc (8.46) Some VCOs are designed for a control voltage centred on 0 V, at which point they gener- ate their ‘free-running’ frequency, ƒFR. This is shown in Figure 8.26(a). For a linear type VCO, the output frequency is given by ƒ = ƒFR + kovc (8.46a) Positive control voltages may increase the frequency, and negative ones decrease it, result- ing in a positive value for ko; or the converse may be true with ko negative. Fig. 8.26 Transfer characteristics of linear VCOs: (a) vc = 0 for ƒFR and a positive control slope; (b) vc ≠ 0 for ƒFR and a negative control slope Phase lock loops 389 Fig. 8.27 Basic phase lock loop Other VCOs have a control voltage range centred on a non-zero voltage. Figure 8.26(b) shows an example of this type of transfer characteristics. In this case and because of the negative slope ƒ = ƒFR – kovc (8.46b) Note: In each case, the slope of the characteristic ∂ƒ/∂vc gives ko. 8.13.8 Loop gain and static phase error At this stage, it would be prudent if we consolidate what we have discussed using the diagram shown in Figure 8.27. For clarity of understanding, we will consider the PLL initially as locked and tracked. Later we will consider how the PLL becomes locked. In Figure 8.27, each block has its own gain parameters. From Equation 8.40, we know that the phase detector develops an output parameter (vd) in response to a phase difference (qe) between the reference input (ƒi) and the VCO frequency (ƒo). The transfer gain (kf) has units of volt/radians of phase difference. At this locked stage, the main function of the filter is simply to remove ƒi, ƒo and the sum of these frequencies. We will temporarily ignore the parameters of the filter in the dashed block of Figure 8.27 because in the locked state, the filter has a parameter of unity. The amplifier has a gain of kA and its unit of gain (Vo/Vd) is dimensionless. Thus Vo = kAvd. The VCO free-running frequency is ƒFR. The VCO frequency (ƒo) will change in response to an input voltage change. The transfer gain (ko) has units of Hertz/volt. The loop gain (kL) for this system is simply the product of the individual blocks: kL = kf kAko (8.47) The units for kL = (v/rad) (v/v) (Hz/v) = Hz/rad. In the diagram ƒi is the input reference frequency to the phase detector and the system is in the locked stage. If the frequency difference before lock was Dƒ = ƒi – fFR, then a volt- age vc = Dƒ/ko is required to keep the VCO frequency equal to ƒi. The amplifier must supply this vc so its input must be vc/kA and this is the output voltage (Vd) required from the phase detector. Summing up vd = vc/kA = (Dƒ/ko)/kA = Dƒ/(kokA) (8.48) 390 Oscillators and frequency synthesizers To produce vd, we would need a phase difference error of qe radians between ƒi and ƒo because kf = vd/qe or vd = kfqe and substituting this in Equation 8.48 yields qe = Dƒ/(kokAkf) and using Equation 8.47, we get Dƒ Dƒ qe = ——— = — — (8.49) kokAkf kL 8.13.9 Hold-in range of frequencies The hold-in range of frequency (Dƒ in Equation 8.49) is defined as the frequency range within which the VCO can drift before it becomes out of lock and stops being controlled by ƒi. In practical circuits, the hold-in frequency range is limited by the operating range of the phase detector because the VCO has a much wider frequency range of operation. In all of the types of phase detector described in Section 8.13.4, except for the flip-flop type, the useful phase–difference range is limited to èp/2. Outside this range, the slope of the phase detector’s characteristic changes, altering the loop feedback from negative to positive, and causing the loop to lose lock. So the static phase error qe is limited to èp/2. Re-arranging Equation 8.49 for qe we get Dƒ = qekL (8.50) For the AND gate type phase detector, where qe has its maximum possible value of èp/2, Dƒ is the maximum possible deviation, Dƒmax = (èp/2)(kL) and its hold-in range = èp/2 × (d.c. loop gain). For the flip-flop type, the static phase error (qe) is limited to èp, and its hold-in range = èp × (d.c. loop gain). Again from Equation 8.50, you can see that if you want a wide hold-in frequency range, then you should increase the loop gain (kL). This is true but care should be exercised in doing this because too high a loop gain will result in loop instability. Let us now consoli- date our thoughts by carrying out Example 8.5. Example 8.5 Example 8.5 summarises much of the information acquired on PLL at this stage. Figure 8.28 provides enough information to calculate the static behaviour of a phase locked loop. Calculate (a) the voltage gain (ka) for the op-amp, (b) the loop gain (kL) in units of second–1 and in decibels (w = 1 rad/s). (c) With S1 open as shown, what is observed at vo with an oscilloscope? (d) When the loop is closed, determine: (i) the VCO output frequency; (ii) the static phase error (qe) at the phase comparator output; (iii) Vo. (e) Calculate the hold-in range Dƒ (assume that the VCO and op-amp are not saturating). (f) Determine the maximum value of vd. (a) Using Equation 8.44 kA = (Rf/R1) + 1 = (9 kΩ/1 kΩ) + 1 = 10 Phase lock loops 391 ko = –40 kHz/v Fig. 8.28 Closed loop system (b) Using Equation 8.47 kL = kfkAko = (0.12 v/rad)(10)(–40 kHz/v) = –48 000 Hz/rad 48 000 cycles/sec 48 000 cycles/sec = ———————— = ———————— rad cycles/(2p) = [2p × 48 000] s–1 = 301 593 s–1 and in terms of dB at 1 rad, we have kL = 20 log (301 593) ≈ 109.6 dB at 1 rad/s (c) With S1 open, there is no phase lock. If we assume that ƒo, ƒi and the sum frequencies have been removed by the filter, then all that will be seen is the beat or difference frequency ƒo – ƒi = 120 kHz – 100 kHz = 20 kHz. (d) (i) When the loop is closed and phase locked, then by definition ƒo = ƒi and since ƒi = 100 kHz, it follows that ƒo = 100 kHz. There is no frequency error but there is a phase error between the two signals. (ii) The free-running frequency fFR of the VCO = 120 kHz. For the VCO output to be 100 kHz, we transpose Equation 8.45 to give Vo = Dƒ/ko = (100 – 120) kHz/(–40 kHz/V) = 0.500 V We want vd, the input to the amplifier whose gain = 10. Using Equation 8.48 vd = vo/kA = 0.5 V/10 = 0.050 V Finally, using Equation 8.40 and transposing it, we obtain qe = vd/kf = 0.050 V/0.12 V/rad = 0.417 radians Alternatively, we could have used Equation 8.49 where 392 Oscillators and frequency synthesizers Dƒ (100 – 120) kHz qe = —— = ——————— —— —————— = 0.417 rad kokAkf (–40 kHz/V)(0.12 V/rad) (10) (iii) Vo was calculated in (ii) as 0.500 V d.c. (e) Since the VCO and op-amp are assumed not to be saturating, then the limitation will obviously depend on the phase detector output. Clearly vd can only increase until vd → vmax = A, at which point qe = p/2. Beyond this point, vd decreases for increasing static phase error, and the phase detector simply cannot produce more output voltage to increasing ƒo, and the loop breaks lock. The total hold-in range is èp/2 or p radi- ans. The total hold-in frequency range between these two break-lock points can be found by using Equation 8.50: Dƒ = qekL = (p) (–40 kHz/V)(0.12 V/rad)(10) = 48.00 kHz In the answer, I have dropped the minus sign because we are only interested in the frequency range. (f) At the frequency where qe = p/2, we have vd(max) = A. Therefore vd = kfqe = 0.12 V/rad × p/2 rad = 0.188 V d.c. This example shows clearly the conditions existing within a phase locked loop system when it is in lock. Summary. Example 8.5 has shown clearly what happens in a phase locked loop when it is in lock. Certain facts are required to make a PLL function correctly. • The sensitivity of the phase locked loop detector (kf) must be known. It can be obtained from measurement or calculation. • The amplifier gain (kA) must be known. This can be obtained by calculation or measure- • The sensitivity of the VCO must be known. The usual way to obtain this is by measurement. • The hold-in range (Dƒ) must be known or measured. • If the oscillator drifts outside this range either due to noise, instability, temperature, etc., then the phase locked loop will be erratic and will break lock and behave like a free- running oscillator. The above conditions are basic to a phase locked loop when it is in a hold-in range situation. Lock-in range The lock-in range is defined as the range of input frequencies over which an unlocked loop will acquire lock. If ƒh and ƒL are respectively the highest and lowest frequencies at which the loop will attain lock, then lock-in range = ƒh – ƒL The lock-in range is usually smaller than the hold-in range. In practice when loop-lock is lost, the PLL generates a saw-tooth wave to sweep the VCO in the hope that lock-in may be re-captured. There are many problems to be considered in acquiring frequency-lock. These include frequency sweep range, step response time, loop bandwidth frequency response, loop Frequency synthesizers 393 bandwidth gain, and the response of the individual components to the sweep range. The VCO phase response is important because its phase gain falls off with an increase in frequency sweep. The loop filter is also extremely important because it determines the step response time and hence the settle-time of the VCO to its new frequency. The PLL is a very complicated system and to properly design such a system, the designer has to take into account many of the problems mentioned above. We do not propose to do it here because we have achieved our aim of showing the principles of a phase lock loop system. However, if you want an extensive source of material that covers phase lock loop design techniques, consult F. M. Gardner’s Phaselock Techniques.11 8.14 Frequency synthesizers 8.14.1 Introduction A frequency synthesizer is a variable-frequency oscillator with the frequency stability of a crystal-controlled oscillator. Synthesizers are used in radio transmitters and receivers because of their output signal stability which is essential in today’s narrow band commu- nication systems. In fact, modern communication systems cannot exist without them. Two basic approaches are used in the design of synthesizers. They are the direct method and the indirect method. The direct method generates the output signal by combining one or more crystal-controlled oscillator outputs with frequency dividers/comb generators, filters and mixers. The indirect method utilises a spectrally pure VCO and programmable phase locked circuitry. Although slower than the direct approach and susceptible to f.m. noise on the VCO, indirect frequency synthesis using the phase lock loop principle is less expensive, requires less filtering, and offers greater output power with lower spurious harmonics. 8.14.2 The direct type synthesizer This type uses no PLLs or VCOs, but only harmonic multipliers, dividers and filters. It may use only one crystal oscillator, with multiple harmonic multipliers and dividers, or it may use several crystal oscillators. An example of the single crystal type is shown in Figure 8.29. The 1 MHz crystal oscillator is followed by a harmonic multiplier, or comb generator. This is a circuit which ‘squares-up’ the signal from the crystal oscillator to generate a train of pulses, rich in harmonics of the crystal frequency. It is called a comb generator because its frequency spectrum resembles a comb. Harmonic selector filter 1 (HSF 1) allows harmonics of the 1 MHz signal to appear at 1 MHz intervals. Hence, by adjusting the filter, it is possible to get frequencies of 1, 2, 3, 4, etc. MHz. This selection of 1 MHz is rather a coarse adjustment. The second output of the 1 MHz crystal oscillator is divided down to 100 kHz, fed to another comb generator and into harmonic selector filter 2 (HSF 2). This filter allows 100 kHz harmonics to pass throught it. The harmonic selected is dependent on the setting of the filter. The two outputs from harmonic selector filter 1 and harmonic selector filter 2 are then mixed to produce sum and difference frequencies, amplified and filtered through the 11 Gardner’s book (1966) is published by John Wiley & Sons. It is old but it remains the classic on phase lock 394 Oscillators and frequency synthesizers Fig. 8.29 An early direct frequency synthesizer output filter. For example, if an output frequency of 6.5 MHz is required. The 6th harmonic of 1 MHz will be selected by (HSF 1), i.e. 6 MHz, and the 5th harmonic of 100 kHz will be selected by (HSF 2), i.e. 500 kHz. The two frequencies are fed into the mixer to produce sum 6.5 MHz and difference frequency 5.5 MHz. The four signals, 500 kHz, 5.5 MHz, 6 MHz and 6.5 MHz, are amplified but the switchable output filter rejects all but the desired 6.5 MHz signal. The frequency resolution can be improved still further by adding further divider, comb generator and filter sections. For instance, a second decade divider and comb generator would provide 10 kHz steps, selectable by a second filter. Its output would be mixed with the output of the 100 kHz step filter in a second mixer, whose output would be filtered to select the sum or difference frequency. This would then be mixed with the selected 1 MHz step in the first mixer. Thus this circuit would provide frequencies up to 10.99 MHz, with 10 kHz resolution. The biggest disadvantage of such a system is that it places stringent requirements on the output filter. This is because, in some cases, the sum and difference frequencies can differ by very little and selecting one frequency and rejecting the other means extremely steep filter slopes. Example 8.6 A synthesizer with four decade divider, comb generator and harmonic filter sections has a crystal oscillator frequency of 10 MHz. State the frequency which could be selected by each section to produce a final output at 75.48 MHz, assuming the sum frequency is selected from each mixer output. State also the frequencies at the output of each mixer, and the frequency selected by the filter following each mixer. Solution. Assuming that the sum frequency is selected from each mixer output, the frequencies are: Frequency synthesizers 395 Section 1: 70 MHz Section 2: 5 MHz Section 3: 400 kHz Section 4: 80 kHz Mixer 3: (400 è 80) kHz = 480 kHz and 320 kHz After filter 3: 480 kHz Mixer 2: (5 è 0.48) MHz = 5.48 MHz and 4.52 MHz After filter 2: 5.48 MHz Mixer 1: (70 è 5.48) MHz = 75.48 MHz and 64.52 MHz After filter 1: 75.48 MHz 8.14.3 Direct digital waveform synthesis The system described in Section 8.14.2 is clumsy and is seldom used today. This is a more recent technique which synthesises a sine wave digitally. The basic principle is illustrated in Figure 8.30. Values of the sine function, at regularly-spaced angular intervals over one complete cycle, are stored digitally in a look-up table, typically in ROM. The values are clocked sequentially out of the look-up table to a digital-to-analogue convertor and via a filter to the output. The filter removes clock-frequency components. The output frequency ƒo = ƒc/S, where ƒc is the clock frequency and S is the number of samples per cycle stored in the look-up table. So the output frequency is determined by the clock frequency. This can be changed by changing the division factor of the program- mable counter, which divides the crystal oscillator frequency ƒref by the factor N. Thus the output frequency is ƒo = ƒref /S N. The value of S must be at least 4, but preferably 10 or so, unless complicated tuneable analogue filtering is used, which would defeat the object of the cheap digital chip. Clearly, this type of synthesizer cannot produce frequencies much higher than, say, 100 MHz because the clock must run at S times the output frequency, and the fast test digital Fig. 8.30 Basic direct synthesizer using sinusoidal waveform synthesis 396 Oscillators and frequency synthesizers Fig. 8.31 Basic PLL synthesizer circuits limit is currently about 2 GHz. In practice, a look-up table in such fast circuitry is currently too expensive, and the digital technique’s cost advantage is realised only at lower 8.14.4 Indirect synthesizers (phase-lock types) These synthesizers use phase lock loops to control voltage-controlled oscillators, with good spectral purity, at frequencies locked to harmonics or sub-harmonics of crystal oscillators. Single loop type The simplest example is the single loop type of Figure 8.31 where a digital counter type frequency divider, set to divide by a programmable factor N, follows the VCO. The loop keeps the divider’s output frequency equal to the crystal frequency (ƒref) so the output frequency from the VCO is an integer multiple (harmonic) of the crystal frequency: ƒo = Nƒref. The output frequency can be changed by changing the division factor N of the divider. The highest output frequency is ƒo = Nmax ƒref, where Nmax is the maximum division capac- ity of the counter. The frequency resolution, which is the minimum output frequency step size, is equal to the crystal frequency ƒref. All the previous analysis of PLLs applies to this loop, but with the added complication that the loop gain is divided by the factor N, so the loop gain changes as the output frequency is changed. Because of this, the loop filter must be designed to maintain loop stability in the worst case. As the output frequency is raised, N is increased, which lowers the loop gain and the loop crossover frequency. So, if a lead-lag filter is used, its break points must be chosen well below the lowest loop crossover frequency, which is obtained at the highest output frequency. The simple single loop synthesizer of Figure 8.31 cannot produce output frequencies any higher than can he handled by the digital divider. With moderately-priced TTL-variant programmable counters, this limits the frequency to the order of 100 MHz. A simple modification called pre-scaling enables higher frequency VCOs to be used. Figure 8.31 shows an example. This synthesizer is used to generate the local-oscillator frequency for a UHF television receiver. The broadcast vision carriers12 have frequencies 12 Television channels and television channel spacing differ in different parts of the world and you should only take this frequency as representative. Frequency synthesizers 397 Fig. 8.32 A PLL synthesizer using pre-scaling, for generating the local-oscillator signal for a television receiver from 471.25 to 847.25 MHz, spaced at exactly 8 MHz intervals. With a receiver vision i.f. of 39.75 MHz, the local oscillator must be tuneable over the range 511 to 887 MHz, assuming it works above the carrier frequency. The pre-scaler is a high speed divider using ECL or Gallium Arsenide (GaAs) circuitry, which can work at these frequencies. It divides by a fixed factor M. The output frequency is now ƒo = MNƒref, and the frequency resolution is increased to Mƒref. We still have ƒo = (N × resolution), as with the simple loop. The poorer resolution is not a problem in this case, because the TV channels are spaced 8 MHz apart. However, 8 MHz does not divide integrally into the required local-oscillator frequencies, so a frequency resolution must be chosen which does. The highest such frequency is 1 MHz, so this is the choice for the resolution, although of course the chan- nel control logic will restrict N to selecting just channel frequencies at 8 MHz intervals. A value of 64 is chosen for M, to reduce the highest local-oscillator frequency down to less than 20 MHz so that a cheap, low power TTL or CMOS chip can be used for the variable divider. Since resolution = Mƒref, we have 1 MHz = 64ƒref, making ƒref = 15.625 kHz. This is best obtained from a cheap, higher frequency crystal and divider, such as a 1 MHz crys- tal with a divide-by-64 counter. Example 8.7 Calculate the values of N to produce the lowest and the highest required local-oscillator ƒo = MNƒref = resolution ƒo = N × resolution = N × 1 MHz and N = ƒo/1 MHZ 398 Oscillators and frequency synthesizers The lowest local-oscillator frequency is 511 MHz, so N = 511. The highest local-oscilla- tor frequency is 887 MHz, so N = 887. 8.14.5 Translation loops: frequency offset using heterodyne Another technique for avoiding the need for a VHF programmable divider is to translate the output frequency down to a lower frequency by mixing with a stable ‘offset’ oscillator. Figure 8.33 shows the principle. The balanced mixer output contains the sum and differ- ence frequencies, ƒo + ƒosc and ƒo – ƒosc, is of the same order as ƒo then (ƒo + ƒosc) is much greater than (ƒo – ƒosc), and a simple low pass filter following the mixer can remove the sum easily, leaving only the difference frequency at the input to the divider. The loop containing the frequency-translation circuitry is called a translation loop. In the example shown in Figure 8.33, the synthesizer is used as the local oscillator for a VHF FM receiver. The carrier signal band is 88.0–108.0 MHz, and the i.f. is 10.7 MHz so, with the local-oscillator frequency above the received frequency, the synthesizer must tune from 98.7 to 118.7 MHz. With ƒosc = 80 MHz, the divider input frequency (ƒo – ƒosc) ranges from 18.7 to 38.7 MHz. The required resolution is 50 kHz, so the reference frequency is chosen as 50 kHz. This could be obtained by dividing from a 1 MHz crystal. In that case the 80 MHz source would be a separate crystal. Alternatively, one crystal oscil- lator running at 16 MHz could have its frequency multiplied and the appropriate harmonic (the fifth in this case) selected for the offset source, and its frequency divided for the refer- ence source. Example 8.8 Calculate the lowest and highest values of the division factor N of the divider in the Fig. 8.33 A PLL synthesizer using an offset oscillator to generate the local oscillator for a VHF FM receiver Summary 399 Solution. The lowest frequency at the divider input is 18.7 MHz and the divider output is 50 kHz, so in this case N = 18.7 MHz/50 kHz = 374. The highest frequency at the divider input is 38.7 MHz, so in this case N = 774. 8.15 Summary This part has been mainly devoted to the more popular types of oscillators. The configu- rations discussed have included the Wien, phase shift, Hartley, Colpitts, Clapp, crystal and the phase locked loop. Frequency synthesizers and their basic operating configurations have also been shown. Oscillator design, particularly phased lock loop synthesizers, is a specialist subject but the information presented in this chapter has provided sufficient background information to allow further study. Further topics 9.1 Aims The primary aim of this chapter is to provide an introduction to signal flow graph analysis so that you will be able to analyse more complicated networks and to follow more advanced publications and papers. The secondary aim of this chapter is to offer you some comments on the use of small software packages in high frequency and microwave engineering. 9.2 Signal flow graph analysis 9.2.1 Introduction Occasions often arise where a network is extremely cumbersome and difficult to under- stand, and it is hard to solve the circuit parameters by algebraic means. In such cases, signal flow graph analysis is used to help understanding, and to reduce circuit complex- ity until it can be handled easily by more conventional algebraic methods. Signal flow analysis is used as a means of writing and solving linear microwave network equations. It is direct and relatively simple; variables are represented by points and the inter-relations between points are represented by directed lines giving a direct picture of signal flow. The easiest way to understand signal flow manupulation is by exam- ples and in the following sections, we will show you several methods of applying signal flow analysis. You are already familiar with Figure 9.1 which was used when we introduced you to Fig. 9.1 General microwave two-port network showing incoming and outgoing waves Signal flow graph analysis 401 Fig. 9.2 Alternative signal flow graph for a two port network scattering parameters. Figure 9.1 gives a semi-pictorial view of s-parameters. An alterna- tive representation of Figure 9.1 is shown in Figure 9.2. This figure is often used in signal flow analysis because of its greater simplicity. Figure 9.2 shows a two-port network with wave a1 entering port 1 and wave a2 entering port 2. The emerging waves from the corre- sponding ports are represented by b1 and b2. Figure 9.3 is a signal flow graph representation of Figure 9.2. In Figure 9.3 each port is represented by two nodes. Node an represents the wave coming into the device from another device at port n and node bn represents the wave leaving the device at port n. A directed branch runs from each a node to each b node within the device. Each of these branches has one or more scattering coefficients associated with it. The coefficient/s shows how an incoming wave gets changed to become an outgoing wave at the node b. Scattering coeffi- cients are complex quantities because they represent both amplitude and phase changes associated with a branch. The value of a wave at a b node when waves are coming in at both a nodes is the superposition of the individual waves arriving at b from each of the separate a nodes. As you already know the relationship of the emergent waves to incident waves is writ- ten as the linear equations b1 = s11a1 + s12a2 (9.1) b2 = s21a1 + s22a2 (9.2) These are called scattering equations and the smns are the scattering coefficients. By comparing Equations 9.1 and 9.2 and Figure 9.3 it is seen that s11 is the reflection coefficient looking into port 1 when port 2 is terminated in a perfect match (a2 = 0). Similarly s22 is the reflection coefficient looking into port 2 when port 1 is terminated in a perfect match (a1 = 0). Fig. 9.3 Signal flow representation of Figure 9.2 402 Further topics Fig. 9.4 Cascading of networks The parameter s21 is the transmission coefficient from port 1 to port 2 when port 2 is terminated in a perfect match (a2 = 0), and s12 is the transmission coefficient from port 2 to port 1 when port 1 is terminated in a perfect match (a1 = 0). Networks are cascaded by joining their individual flow graphs as in Figure 9.4. Note how a′2 is synonymous with b2 and how b′2 is synonymous with a2. This can be shown by a connecting branch of unity. See Figure 9.4. 9.2.2 Signal flow representation of elements Some examples of transmission line elements and their equivalent signal flow graphs are shown in Figures 9.5 to 9.10. In Figure 9.5, r represents the magnitude of the reflection coefficient. The phase change produced by the termination is shown as ejfL where fL represents the load phase change in Fig. 9.5 Signal flow graph representation of a termination Figure 9.6 shows a length of lossless transmission line which has no reflection coeffi- cient. When compared to the flow graph of Figure 9.7, the s11 and s22 branches have the value zero or can be left out entirely. The term e–jfL represents the phase change within the Fig. 9.6 Signal flow graph of a length of lossless transmission line Figure 9.7 shows a detector and k denotes the scalar conversion efficiency relating the incoming wave amplitude to a meter reading. The meter reading M is assumed calibrated to take into account the detector law so k is independent of level. Signal flow graph analysis 403 Fig. 9.7 Signal flow graph of a detector Figure 9.8 shows the signal flow graph for a shunt admittance. Fig. 9.8 Signal flow graph of a shunt admittance Figure 9.9 shows the signal flow graph for a series impedance. Fig. 9.9 Signal flow graph of a series impedance Figure 9.10 shows a flow graph representation of a generator. In microwave systems, it is generally more convenient to think of a generator as a constant source of outward trav- elling wave with a reflection coefficient looking back into the generator output. Fig. 9.10 Signal flow graph of a generator 9.2.3 Topological manipulation of signal flow graphs The method of finding the value of a wave at a certain node may be arrived at with a series of topological manipulations which reduce a flow graph to simpler and simpler forms until the answer is apparent or until such a stage is reached when Mason’s non-touching rule 404 Further topics can be used easily. Mason’s rule will be explained later. Four rules are given for easier understanding of signal flow manipulations. Rule I: Branches in series (where the common node has only one incoming and one outgoing branch) may be combined to form a single branch whose coefficient is the prod- uct of the coefficients of the individual branches. A typical example of this is shown in Figure 9.11 where E2 = S21E1 E3 = S32E2 E3 = S32S21E1 (9.3) Fig. 9.11 Branches in series Rule II: Two branches pointing from a common node to another common node (branches in parallel) may be combined into a single branch whose coefficient is the sum of the indi- vidual coefficients. A typical example of this is shown in Figure 9.12 where Fig. 9.12 Branches in parallel E2 = SAE1 E2 = SBE1 E2 = (SA + SB)E1 (9.4) Fig. 9.13 Reduction of a feedback loop Rule III: When node n possesses a self loop (a branch which begins and ends at n) of coefficient Snn the self loop may be eliminated by dividing the coefficient of every other branch entering node n by (1 – Snn). A typical example of this is shown in Figure 9.13 where the loop S22 at node E2 may be eliminated by dividing the coefficient (S21) entering the node E2, by (1 – S22). Signal flow graph analysis 405 Rule IV: A node may be duplicated, i.e. split into two nodes which may be subsequently treated as two separate nodes, providing the resulting signal flow graph contains, once and only once, each combination of separate (not a branch which forms a self loop) input and output branches which connect to the original node. Any self loop attached to the original node must also be attached to each of the nodes resulting from duplication. A typical example is shown in Figure 9.14(a) to (e) where a complicated signal flow graph is reduced to that of a far simpler one. Fig. 9.14 Node duplication with a feedback loop: (a) original graph; (b) duplication of node E3 ; (c) elimination of node E ’3 to form a self loop; (d) duplication of node E2 with self loop; (e) elimination of self loops 406 Further topics 9.2.4 Mason’s non-touching loop rule Mason’s non-touching loop rule is extremely useful for calculating the wave parameters in a network. At first glance, Mason’s expression appears to be very frightening and formi- dable but it can be easily applied once the fundamentals are understood. Some of the fundamentals relating to this rule have already been discussed in the preceding sections but for the sake of clarity, some of the material will be repeated in the application of Mason’s rule to the example given in Figure 9.15 which shows the flow diagram of a network cascaded between a generator (E) and a load (GL). Fig. 9.15 Signal flow representation of a network When networks are cascaded it is only necessary to cascade the flow graphs since the outgoing wave from the earlier network is the incoming wave to the next network. In Figure 9.15, the system has only one independent variable, the generator amplitude (E). The flow graph contains paths and loops. A path is a series of directed lines followed in sequence and in the same direction in such a way that no node is touched more than once. The value of the path is the product of all coefficients encountered en route. In Figure 9.15, there is one path from E to b2. It has the value S21. There are two paths from E to b1, namely S11 and S21GLS12. A first-order loop is a series of directed lines coming to a closure when followed in sequence and in the same direction with no node passed more than once. The value of the loop is the product of all coefficients encountered en route. In Figure 9.15, there are three first-order loops, namely GgS11, S22GL, and GgS21GLS12. A second-order loop is the product of any two first-order loops that do not touch at any point. In Figure 9.15, there is one second-order loop, namely GgS11S22GL. A third-order loop is the product of any three first-order loops which do not touch. There is no third-order loop in Figure 9.15. An nth-order loop is the product of any n first-order loops which do not touch and so on. The solution of a flow graph is accomplished by application of Mason’s non-touching loop rule1 which, written symbolically, is P1[1 – ∑L(1)(1) + ∑L(2)(1) – ∑L(3)(1) + . . .] + P2[1 – ∑L(1)(2) + ∑L(2)(2) . . . ] + P3[1 – ∑L(1)(3) + . . .] T = —————————————————————————————————————————— 1 – ∑L(1) + ∑L(2) – ∑L(3) + . . . 1 Do not panic! Detailed examples follow. If you really want to know more about this topic see Mason, S.J., ‘Feedback theory – some properties of signal flow graphs’. Proc. IRE (41) 1144–56, Sept 1953. See also Mason, S.J., ‘Feedback theory – further properties of signal flow graphs’. Proc. IRE (44) 920–26, July 1956. Signal flow graph analysis 407 Here, P1, P2, P3, etc. are the values of all the various paths which can be followed from the independent variable node to the node whose value is desired. ∑L(1) denotes the sum of all first-order loops. ∑L(2) denotes the sum of all second- order loops and so on. ∑L(1)(1) denotes the sum of all first-order loops which do not touch P1 at any point, and so on. ∑L(2)(1) denotes the sum of all second-order loops which do not touch P1 at any point, the superscript (1) denoting path 1. Similarly, ∑L(1)(2) denotes the sum of all first-order loops which do not touch P2 at any point and so on. In other words, each path is multiplied by the factor in brackets which involves all the loops of all orders which that path does not touch. T is a general symbol representing the ratio between the dependent variable of interest and the independent variable. This process is repeated for each independent variable of the system and the results are summed. As examples of the application of the rules in Figure 9.15, the transmission b2/E and the reflection coefficient b1/a1 are written as follows: b2 S21 —— = ——————————————————— (9.6) E 1 – GgS11 – S22GL – GgS21GL S12 + Gg S11S22GL b1 S11(1 – S22GL) + S21GLS12 S12S21GL ——= ——————————— = S11 + ———— (9.7) a1 1 – S22GL 1 – S22GL Note that the generator flow graph is unnecessary when solving for b1/a1, and the loops associated with it are deleted when writing this solution. It is worth mentioning at this point that second- and higher-order loops can quite often be neglected while writing down the solution if one has orders of magnitude for the components in mind. 9.2.5 Signal flow applications Signal flow graphs are best understood by some illustrative examples. Example 9.1 Figure 9.16 illustrates a simple system where a generator is connected to a detector. The signal flow graph for the system is illustrated in Figure 9.17. It is made up from the basic Fig. 9.16 Generator and detector system Fig. 9.17 Signal flow graph for system of Figure 9.16 408 Further topics building blocks of the generator and detector illustrated in Figures 9.7 and 9.10. The phase of the generator is not considered for ease of understanding. By inspection, and by using Rules I and III, you can readily see that [ ] M1 = Eg ———— k (9.8) 1 – ρg ρ d Example 9.2 Fig. 9.18 Generator, two-port network and detector Fig. 9.19 Signal flow graph of system of Figure 9.18 Figure 9.18 depicts the case where a two port network is placed between the generator and the detector. The signal flow graph of Figure 9.19 is again made up from the basic build- ing blocks of Figures 9.3, 9.7 and 9.10. Note particularly that we have used the signal flow graph of Figure 9.3 for the two-port network but for ease of working have replaced the S- parameters, s11, s21, s22, s12, with r1, T, r2, T, respectively. In Figure 9.20, nodes (2) and (4) have been duplicated into nodes (2′), (2″), (4′), (4″) by Rule IV. Figure 9.21 follows from the sequence of manipulations below. Fig. 9.20 Simplification process 1 1 Eliminate node (4′) by Rule I giving a self loop at node (3) of the value ρd ρ2. 2 Eliminate this self loop by Rule III changing the value of the branch node (1) to node (3) from T to T/(1 – ρd ρ2). 3 Eliminate node (2′) by Rule I giving a self loop at node (1) of value ρg ρ1. 4 Eliminate this self loop by Rule III changing the value of the branch leading from the generator to 1/(1 – ρg ρ1) and also changing the branch from node (2″) to node (1) to ρg/(1 – ρg ρ1). Signal flow graph analysis 409 5 Eliminate nodes (2″) and (4″) giving a branch from node (3) to node (1) of value (Tρgρd)/(1 – ρg ρ1). Fig. 9.21 Simplification process 2 Figure 9.22 shows the duplication of node (3) into nodes (3′) and (3″). Fig. 9.22 Simplification process 3 Figure 9.23 shows the signal flow graph which results from eliminating node (3″) by Rule I and then eliminating the resulting self loop at node (1) by Rule III. Fig. 9.23 Simplification process 4 In Figure 9.23, there now exists a single path from Eg to M2 and nodes (1) and (3) can be eliminated by Rule 1 yielding: Eg Tk M2 = ⎡ T 2 ρg ρd ⎤ (1 − ρg ρ1 )⎢1 − ⎥(1 − ρd ρ2 ) ⎢ (1 − ρd ρ2 )(1 − ρg ρ1 ) ⎥ ⎣ ⎦ which simplifies to ⎡ 1 ⎤ M2 = Eg kT ⎢ 2 ⎥ (9.9) ⎣1 − ρg ρ1 − ρd ρ2 − T ρg ρd + ρg ρd ρ1ρ2 ⎦ ⎢ ⎥ 410 Further topics 9.2.6 Summary on signal flow graphs The chief advantages of signal flow graphs over matrix algebra in solving cascaded networks are the convenient pictorial representations and the painless method of proceed- ing directly to the solution with approximations being obvious in the process. As your study in microwave engineering continues, you will come across more and more examples on the use of S-parameters and signal flow techniques. 9.3 Small effective microwave CAD packages 9.3.1 Introduction The subject of software is a volatile one because new programs are being constantly intro- duced, old programs are constantly being updated, and last but not least, personal prefer- ences come into the choice of a particular program. Excellent radio engineering computer programs such as Hewlett Packard Design System 85150 series, EEsof’s Libra*, Touchstone*, Super Compact*, and Academy* have been available for many years. These programs are excellent and extremely versatile. However, these facilities cost money and require quality computers with large RAM and disk facilities. If you or your company can afford these systems then by all means go for one or more of these software packages. If you have an average personal computer with average RAM and only a little money, consider intermediate software programs such as ARRL (American Radio Relay League) ‘ARRL Radio Designer’, or Barnard’s Microwave System’s ‘Wavemaker’ or Number One System’s ‘Z match for Windows (Professional)’. The ARRL’s program is a subset of ‘Super Compact’ and is quite powerful. If your frequency usage is not confined to microwave systems, then consider general purpose programs such as ‘PSpice’, ‘HSpice’ and ‘Spice Age’ which incorporate limited Smith chart facilities. If money is nearly non-existent, then look in the Internet for free programs. Some of these programs are excellent. You can also go to the large commercial firms and enquire about the possibility of hiring software programs for a limited period. In some cases, it is possible to obtain reduced rates for educational establishments. Some firms such as Hewlett Packard offer internet sites where universities send in examples of their teaching and research work and may offer free copies of the programs they have developed. Some firms may offer you the free use of their small programs for a limited period. Many people and some small radio engineering courses cannot afford even these costs. In long distance learning situations, software expenditure becomes doubly important because each student must be provided with programs which can be run on their home computers. Therefore low cost, small, powerful packages requiring minimum storage and RAM requirements are vitally important. For personal and home use, I use inexpensive but relatively powerful programs such as Hewlett Packard’s AppCAD, CalTech’s PUFF and Motorola’s Impedance Matching Program (MIMP) to investigate and produce simple designs. AppCAD is useful for the calculation of individual components, losses and gains. PUFF is valuable in calculating two port parameters, input and output matches, gains and losses and frequency responses and has plotting facilities for layout artwork. MIMP provides real time facilities for narrow and broadband matching using Smith charts and rectangular plots. Small effective microwave CAD packages 411 9.3.2 Hewlett-Packard’s computer aided design program – AppCAD Hewlett-Packard’s Applications Computer Aided Design Program AppCAD is a collection of software tools or modules, which aid in the design of RF (radio frequency) and microwave circuits. AppCAD also includes a selection guide for Hewlett Packard RF and Microwave semiconductors. The modules considered in AppCAD are listed in Figure 9.24. Each main program is listed on the left table while the highlighted item is described on the right table. Fig. 9.24 Screen print-out of AppCAD AppCAD modules The modules considered in AppCAD are as follows. (i) Transistor design data. This module computes various gain and stability data from S-parameters. Input S-parameters can be read from a TOUCHSTONE formatted file or entered manually. S-parameters input from a TOUCHSTONE formatted file may also be modified manually via an edit function. The program • calculates stability circles; • converts S-parameters to Y-parameters, Z-parameters or H-parameters; • calculates Gms and Gml. (ii) Mixer spurious search. Mixers will generate harmonics of the RF input signal and the local-oscillator frequencies. This means that there exists a wide range of frequencies, many of which may lie outside the desired input passband, which will give unwanted responses in the IF band. This module will calculate all spurious responses for user chosen frequencies, passbands, and harmonics of the local oscillator and signal. (iii) Microwave calculator. This is a computerised version of the famous Hewlett Packard ‘Reflectometer’ slide rule calculator. Calculations include reflection coefficients, 412 Further topics standing wave ratios, mismatch loss, return loss, mismatch phase error, coupler directivity uncertainty and maximum standing wave ratio from mismatches. (iv) Microwave path calculations. This module calculates the signal-to-noise (S/N) performance resulting from the following factors: receiver noise figure, antenna gain, transmitter power, path distance, frequency and line losses. The systems covered are one- way (communication) and two-way (radar). (v) Transmission lines. From physical dimensions, this module calculates the following properties: characteristic impedance, effective dielectric constant, electrical line length and coupling factor. The structures covered include microstrip, stripline, coplanar waveguide with and without ground plane and coaxial lines. (vi) Two-port circuit analysis. This easy to use linear circuit analysis program can include lumped or distributed circuit elements, which may be represented by an S-para- meter file in TOUCHSTONE format. The calculated S-parameters can be displayed on the screen and printed. The data can also be graphed on to either a Smith chart or a linear X–Y plot, which can be printed to a Epson compatible printer. (vii) Spiral inductor design. This module calculates the inductance of a circular spiral from its number of turns, conductor width, substrate height, inner radius and dielectric constant. Inductance is calculated for two cases, with and without a ground plane. (viii) Impedance matching. This module determines both lumped and distributed elements for impedance matching of a source impedance and load impedance. The lumped or distributed elements determined are those for either an L-section, T-section, pi-section, transmission line transformer or tandem 3/8 wavelength transformer. (ix) Pin attenuator and switch design. Insertion loss and isolation are calculated from PIN diode characteristics for both the series and shunt configurations. A built-in menu automatically returns the diode parameters from a menu selection of part numbers. Alternatively, custom diode series resistance and junction capacitance may be used. The program calculates the required resistance values for both Pi and bridged T attenuators from the desired attenuation in decibels (dB). (x) Schottky detector calculations. This module calculates the effect of video amplifier characteristics, RF bypassing, amplifier input resistance and voltage sensitivity on pulse response, detected video bandwidth and TSS. (xi) Transistor bias circuits. This module examines bias networks for microwave bi- polar transistors. Bias network resistors are calculated for a given collector current and voltage. The change in collector current with temperature is also computed for each network. Networks covered include non-stabilised, voltage feedback and voltage feedback constant base current. (xii) Noise calculations. This module calculates the cascade noise figure and other performance parameters for a sub-system block diagram such as a receiver. This type of analysis allows system planning for the tradeoffs of important characteristics such as noise Small effective microwave CAD packages 413 figure (sensitivity), gain distribution, dynamic range, signal levels and intermodulation products. Provision is made for system analysis with temperature. (xiii) Thermal analysis. A general introduction to heat transfer is presented with empha- sis on applications to semiconductors. This module includes a tutorial section, thermal resistance calculations for semiconductors, thermal analysis of MIC (hybrid) circuits and a table of thermal conductivities. Details of programs A program listed in Figure 9.24 usually sub-divides into other programs. For example, the transmission lines program of Figure 9.25 sub-divides into seven other types of transmission line. See the right column of Figure 9.25 for a description of the program. Figure 9.25 further sub-divides into another screen for the calculation of seven types of lines (Figure 9.26). Fig. 9.25 Selection of transmission lines program Fig. 9.26 Sub-division of the transmission lines program 414 Further topics Fig. 9.27 Calculation of co-planar waveguide with ground plane Figure 9.27 shows the case for the calculation of co-planar waveguide with a ground The same is true of the microwave calculator program. The selection of this program leads to further sub-division and four separate programs. See Figure 9.28. AppCAD also has facilities for calculating the inductance of spiral inductors. You merely have to state the number of turns and dimensions of your inductor in Figure 9.29 and APPCAD will give you the inductance in the result box. AppCAD is also extremely useful for conversion from one set of parameters to another. Figure 9.30 shows what happens when you select the ‘Transistor Design Data’ program. If you now select the Convert to Y, Z, or H and press the return key. You will now be given a choice of what type of parameters you require. See Figure 9.31. Ensure that the Convert Fig. 9.28 AppCAD’s calculator program Small effective microwave CAD packages 415 Fig. 9.29 Calculating the inductance of spiral inductors Fig. 9.30 Selection of transistor design data Fig. 9.31 Selection of Y-, Z- or H-parameters 416 Further topics Fig. 9.32 Y-parameters of transistor HPMA0285.S2P to Y-parameters line is highlighted. Press the return key and you get Figure 9.32. These parameters have been calculated from the s-parameters supplied by the manufacturer for transistor HPMA0285.S2P. If you had wanted the Z-parameters, then you would have chosen the Convert to Z- parameters line and pressed return to get Figure 9.33. These parameters have been calcu- lated from the s-parameters supplied by the manufacturer for transistor HPMA0285.S2P. Similarly if you had wanted H-parameters, you would have selected the Convert to H- parameters and pressed return to get Figure 9.34. So you can see for yourself how much time and effort can be saved by using AppCAD. In most cases, you might be able to get the program free from Hewlett Packard who own the copyright. The hardware requirements for the program are very modest and the Fig. 9.33 Z-parameters of transistor HPMA0285.S2P Small effective microwave CAD packages 417 Fig. 9.34 H-parameters of transistor HPMA0285.S2P DOS version will even run with an 8086 processor. There is also a Windows version of AppCAD available on the Internet. 9.3.3 PUFF Version 2.1 Fig. 9.35 Feedback amplifier response 418 Further topics Puff Version 2.1 was chosen for this book because of: (i) its ease of use – PC format, (ii) its versatility, (iii) its computer requirement flexibility – ≈290 KB on a floppy disk, any processor from an 8080 to Pentium, choice of display, CGA, EGA or VGA, and (iv) choice of printer, dot-matrix, bubble jet or laser and (v) its low costs. As you have seen for your- self, it can be used for (i) lumped and distributed filter design, evaluation, layout and fabri- cation, (ii) evaluation of s-parameter networks, (iii) lumped and distributed matching techniques, layout and construction, (iv) amplifier design layout and construction and (v) determination of input impedance and admittance of networks. There are also many features to PUFF which have not been used in this book. For exam- ple, PUFF can be used for the design of oscillators; it has compressed Smith chart facili- ties. An example of this is shown in Figure 9.35. If you want further information on PUFF, I suggest you contact PUFF Distribution, CalTech in Pasadena, California, USA. They can supply you with the source code, a manual for the program, and lecture notes for carrying out more advanced work with 9.3.4 Motorola’s Impedance Matching Program (MIMP) MIMP is excellent for narrow-band and wide-band matching of impedances. It has facilities for matching complex source and load impedances and designing lumped or distributed circuits with the desired Q graphically. This program can be explained by an example. Consider the case where the output impedance, ≈(20 + j0) Ω, of a trans- mitter operating between 470 MHZ and 500 MHz is to be matched to an antenna whose nominal impedance is 50 Ω. A return loss of ≈20 dB is required. The conditions are entered into MIMPs as in Figure 9.36. Three frequencies are used to cover the band and the load and source impedances are also entered into the figure. When Figure 9.36 is completed, the ESC key is pressed to move on to Figure 9.37 where a network is chosen. For this case, a T network has been chosen. At this stage, the exact values of the components and the Q of the matching network are unknown so nominal values are inserted. The exact values will be derived later. For clarity, Zin and the load have been annotated in Figure 9.37. After completion of Figure 9.37, the ESC key is pressed to enter Figure 9.38. Starting from the top left line in Figure 9.37, we have SERIES CAP and up/down arrows which allow any component to be selected. C1 is shown in this case. Capacitors are shown in this box with its arrow keys. The next right block shows values of induc- tors. Adjustment is provided by up/down arrow keys. The next right box with its arrow keys is the Q selection box. Q = 3 has been selected. The next box after the logo is the line impedance (Zo) box. Its default position is 10 Ω but it can be changed and the Smith chart plot values will automatically change accordingly. The FREQ box allows selection of frequency. It has been set to mid-point, i.e. 485 MHz. The remaining three boxes are self-evident. The middle left-hand box provides a read-out of impedance at points to the ‘right’ of a junction. The Smith chart return loss circle size is determined by the Return loss boundary set in the lower left box. Arcs AB, BC and CD are adjusted by components C1, C2 and L1 respectively until the desired matching is obtained. Small effective microwave CAD packages 419 Fig. 9.36 Input data for Motorola’s MIMP Fig. 9.37 Matching circuit for Motorola’s MIMP 420 Further topics Fig. 9.38 Smith chart and input return loss The great advantage of MIMP is that matching is carried out electronically and quickly. There are no peripheral scales on it like a conventional paper Smith chart but this is unnec- essary because each individual point on the chart can be read from the information boxes. A good description of how this program works can be found in ‘MIMP Analyzes Impedance Matching Network’ RF Design, Jan 1993, 30–42. MIMP is a Motorola copyright program but it is usually available free from your friendly Motorola agents. The program requirements are very modest with processor 80286 or higher, VGA graphics and 640k RAM. 9.4 Summary of software The above computer aided design programs, namely AppCAD, PUFF and MIMP, are extremely low cost and provide a very good cross-section of theoretical and practical constructional techniques for microwave radio devices and circuits. AppCAD was used extensively for checking the bias and matching circuits. MIMP was used extensively for checking the Smith chart results in the book. I am sure that these programs will be useful additions to your software library. These references are provided as a guide to readers who want more knowledge on the main items discussed in this book. They have been compiled into seven categories. These are circuit fundamen- tals, transmission lines, components, computer aided design, amplifiers, oscillators, and signal flow diagrams. The references are in alphabetical order in each section. References soon become antiquated and to keep up with developments, it is best to read mater- ial, such as the IEEE Transactions on various topics, IEE journals, Microwave Engineering journal, etc. These journals are essential because they provide knowledge of the latest developments in the high frequency and microwave world. Attending conferences is also very important and many large firms like Hewlett Packard, Motorola, and Texas Instruments often provide free study seminars to keep engineers up to date on amplifier, oscillator, CAD and measurement techniques. Many large firms such as Hewlett Packard also provide education material on the Internet. For example, many universities put their experimental work on http://www.hp.com/info/college_lab101. Circuit Fundamentals Avantek 1982: High frequency transistor primer, Part 1. Santa Clara CA: Avantek. Festing, D. 1990. Realizing the theoretical harmonic attenuation of transmitter output matching and filter circuits, RF Design, February. Granberg, H. O. 1980. Good RF construction practices and techniques. RF Design, September/ Hewlett Packard. S parameters, circuit analysis and design. Hewlett Packard Application Note 95, Palo Alto CA: Hewlett Packard. Johnsen, R.J. Thermal rating of RF power transistors. Application Note AN790. Phoenix Az: Motorola Semiconductor Products. Jordan, E. 1979: Reference data for engineers: radio, electronics, computers and communications. Seventh Edition. Indianapolis IN: Howard Sams & Co. Motorola. Controlled Q RF technology – what it means, how it is done. Engineering bulletin EB19, Phoenix AZ: Motorola Semiconductor Products Sector. Motorola 1991. RF data book DL110, Revision 4, Phoenix AZ: Motorola Semiconductor Sector. Saal, R. 1979: Handbook of filter design. Telefunken Aktiengesellschaft, 715 Backnang (Wurtt), Gerberstrasse 34 PO Box 129, Germany. Transistor manual, Technical Series SC12, RCA, Electronic Components and Devices, Harrison NJ, Transmission Lines Babl, I.J. and Trivedi, D.K. 1977. A designer’s guide to microstrip. Micorwaves, May. Chipman, R.A. 1968: Transmission lines. New York NY: Schaum, McGraw-Hill. 422 References Davidson, C.W. 1978: Transmission lines for communications. London: Macmillan. Edwards, T.C. 1992: Foundations for microstrip circuit design. Second Edition. John Wiley & Sons. Ho, C.Y. 1989. Design of wideband quadrature couplers for UHF/VHF. RF Design, 58–61, November (with further useful references). Smith, P.H. 1944. An improved line calculator. Electronics, January, 130. Acrian Handbook 1987. Various Application Notes. The Acrian Handbook, Acrian Power Solutions, 490 Race Street, San Jose CA. Blockmore, R.K. 1986. Practical wideband RF power transformers, combiners and splitters. Proceedings of RF Expo West, January. Fair-Rite. Use of ferrities for wide band transformers. Application Note. Fair-Rite Products Haupt, D.N. 1990. Broadband-impedance matching transformers as applied to high-frequency power amplifiers. Proceedings of RG Expo West, March. Myer, D. 1990. Equal delay networks match impedances over wide bandwidths. Microwaves and RF, April. Phillips, 1969–72. On the design of HF wideband transformers, parts I and II. Electronic Application Reports ECO69007 & ECOP7213. Phillips Discrete Semiconductor Group. Computer aided design CAD Roundtable 1996. Diverse views on the future of RF design. Microwave Engineering Europe Directory, 20–26. Da Silva, E. 1997: Low cost microwave packages. Fourth International Conference, Computer Aided Engineering Education CAEE97, Krakow, Poland. Da Silva, E. 1997: Low cost radio & microwave CAL packages. EAEEIE, Eighth Annual conference, Edinburgh, Scotland. Davis, F. Matching network designs with computer solutions. Application Note AN267. Phoenix AZ: Motorola Semiconductor Sector. Edwards, T.C. 1992: Foundations for microstrip circuit design. Second Edition. John Wiley & Gillick, M., Robertson, I.D. and Aghvami, A.H. 1994. Uniplanar techniques for MMICs. Electronic and Communications Engineering Journal, August, 187–94. Hammerstad, E.O. 1975. Equations for microstrip circuit design. Proceedings Fifth European Conference, Hamburg. Kirchning, N. 1983. Measurement of computer-aided modelling of microstrip discontinuities by an improved resonator method. IEEE Trans MIT, International Symposium Digest, 495–8. Koster, W., Norbert, H.L. and Hanse, R.H. 1986. The microstrip discontinuity; a revised description. IEEE MTT 34 (2), 213–23. Matthei, G.L., Young, L. and Jones, E.M.T. 1964: Microwave filters, impedance matching networks and coupling structures. New York NY: McGraw-Hill. MMICAD (for IBM PCs). Optotek, 62 Steacie Drive, Kanata, Ontario, Canada, K2K2A9. Moline, D. 1993. MIMP analyzes impedance matching networks. RF Design, January, 30–42. Nagel, L.W. and Pederson, D.O. 1973. Simulation program with integrated circuit emphasis. Electronics Research Lab Rep No ERL-M382, University of Calif, Berkeley. PSpice by MicroSim Corporation, 20 Fairbands, Irvine CA 92718. Rutledge, D. 1996: EE153 Microwave Circuits. California Institute of Technology. SpiceAge. Those Engineers Ltd, 31 Birbeck Road, Mill Hill, London, England. Wheeler, H.A. 1977. Transmission line properties of a strip on a dielectric sheet on a plane. IEEE MTT 25 (8), 631–47. References 423 Bowick, C. 1982: RF circuit design. Indianapolis IN: Howard Sams. Carson, R.S. 1975: High frequency amplifiers. New York NY: John Wiley and Sons. Dye, N. and Shields, M. Considerations in using the MHW801 and MHW851 series power modules. Application Note AN-1106. Phoenix AZ: Motorola Semiconductor Sector. Froehner, W.H. 1967. Quick amplifier design with scattering parameters. Electronics, October. Gonzales, G. 1984: Microwave transistor amplifier analysis and design. Englewood Cliffs NJ: Prentice Hall. Granberg, H.O. A two stage 1 kW linear amplifier. Motorola Application Note A758. Phoenix AZ: Motorola Semiconductor Sector. Granberg, H.O. 1987. Building push-pull VHF power amplifiers. Microwave and RF, November. Hejhall, R. RF small signal design using two port parameters. Motorola Application Report AN Hewlett Packard. S parameter design. Application Note 154. Palo Alto CA: Hewlett Packard Co. ITT Semiconductors. VHF/UHF power transistor amplifier design. Application Note AN-1-1, ITT Liechti, C.A. and Tillman, R.L. 1974. Design and performance of microwave amplifiers with GaAs Schottky-gate-field-effect transistors. IEEE MTT-22, May, 510–17. Pengelly, R.S. 1987: Microwave field effect transistors theory, design and applications. Second Edition. Chichester, England: Research Studies Press, division of John Wiley and Sons. Rohde, U.L. 1986. Designing a matched low noise amplifier using CAD tools. Microwave Journal, October 29, 154–60. Vendelin, G., Pavio, A. and Rohde, U. Microwave circuit design. New York NY: John Wiley & Vendelin, G.D., Archer, J. and Bechtel, G. 1974. A low-noise integrated s-band amplifier. Microwave Journal, February. Also IEEE International Solid-state Circuits Conference, February 1974. Young, G.P. and Scalan, S.O. 1981. Matching network design studies for microwave transistor amplifiers. IEEE MTT 29, No 10, October, 1027–35. Abe, H. A highly stabilized low-noise Ga-As FET integrated oscillator with a dielectric resonator in the C Band. IEEE Trans MTT 20, March. Gilmore, R.J. and Rosenbaum, F.J. 1983. An analytical approach to optimum oscillator design using S-parameters. IEEE Trans on Microwave Theory and Techniques MTT 31, August, 663–9. Johnson, K.M. 1980. Large signal GaAs FET oscillator design. IEEE MTT-28, No 8, August. Khanna, A.P.S. and Obregon, J. 1981. Microwave oscillator analysis. IEEE MTT-29, June, 606–7. Kotzebue, K.L. and Parrish, W.J. 1975. The use of large signal S-parameters in microwave oscillator design. Proceedings of the International IEEE Microwave Symposium on circuits and systems. Rohde, Ulrich L. 1983: Digital PLL frequency-synthesizers theory and design. Englewood Cliffs NJ: Prentice Hall. Vendelin, G.D. 1982: Design of amplifiers and oscillators by the S-parameter method. New York NY: John Wiley and Sons. Signal flow Chow, Y. and Cassignol, E. 1962: Linear signal-flow graphs and applications. New York NY: John Wiley and Sons. Horizon House 1963: Microwave engineers’ handbook and buyers’ guide. Horison House Inc, Brookline Mass, T-15. Hunton, J.K. 1960. Analysis of microwave measurement techniques by means of signal flow graphs. Trans IRE MTT-8, March, 206–12. 424 References Mason, S. J. 1955. Feedback theory – some properties of signal flow graphs. Proc IRE 41, 1144–56, Mason, S.J. 1955. Feedback theory – further properties of signal flow graphs. Proc IRE 44, 920–26, Mason and Zimmerman. 1960: Electronic circuits, signals and systems. New York NY: John Wiley and Sons. Montgomery et al 1948: Principles of microwave circuits. New York NY: McGraw-Hill Book Co. AC equivalent circuits, transistors 291, 292 Band-stop filter 222 Active bias circuit 276 design 223 Adjacent channel selectivity 35 Barkhausen criteria 359 Admittance manipulation, on Smith chart 98 Base-voltage potential divider bias circuit 272 Admittance parameters 297 Biasing: Admittance, found using Smith charts 172 bi-polar transistors 275 Aerial amplifier design 300 depletion mode MOSFETS 290 Aerial distribution systems using amplifiers 31 MOSFETs 286 Aerials 14 n-channel FETs 278 Alternative bias point 313 Bipolar transistors 262 Amplifier design 195 biasing 275 broadband amplifiers 349 construction 291 feedback amplifiers 352 Branch line coupler 82, 170 for optimum noise figure 345 Broadband amplifiers, design 349 for specific gain 332 Broadband matching 112 s parameters 321 Broadband matching networks 260 using conditionally stable transistors 313, 314 BT cut 377 with conditionally stable devices 339 Butterworth filter 208 with conjugately matched impedances 322 Butterworth normalized values 210 Amplitude distortion 63 Amplitude modulation 4 Capacitance end effects for an open circuit 191 Analogue-type phase detector 383 Capacitive divider matching 240 AND gate phase detector 383 Capacitive matching 240 Antennas 14 Capacitive stub matching 181 distribution systems 25 Capacitors: AppCAD 411 quality factor 242 AT cut 377 series and parallel forms 242 Attenuation 46, 62 Cascading of tuned circuits 201 Auto-transformers 235 Characteristic impedance 45 Clapp oscillator 372 Balanced antenna 25 Coaxial line 48 Balanced line 26 characteristic impedance 50 Balanced/unbalanced transformer 26 Collector current characteristics 265 Bandpass filter 152, 217 Colpitts oscillator 368 design 218 Combined modulation 9 using microstrip lines 221 Commercial cable 60 426 Index Constant gain circles 333 Gain sensitivity: Co-planar waveguides 47 AND gate 385 Coupled lines 50 flip-flop detector 385 Coupler evaluation, using PUFF software 170 Group velocity 63 Crystal control oscillators 376 Crystal temperature stability 377 Half-power supply principle 268 Crystals 376 Hartley oscillators 271 Current gain, transistors 266, 299 High frequency equivalent circuit of a transistor 294 DC amplifier 386 High-pass filter 214 Depletion mode MOSFETs 288 design 215 Digital phase detectors 383 using microstrip lines 217 Dipole 16 Hybrid p equivalent circuit 294 Direct digital waveform synthesis 395 Direct type synthesizer 393 Image channel interference 39 Directivity of radiation 14 Immittance Smith chart 97 Discontinuities 189 Impedance: in transmission systems 46 conversion to Admittance using Smith chart Dispersion, in transmission systems 46 95 Double stub matching 122 of distributed circuits 106 Double stub tuning, verification using PUFF Impedance manipulation, on Smith chart 94 software 186 Impedance matching 110, 233, 412, 418 Double superhet receivers 40 using a l/4 transformer 111 using a stub tuner 115 Electromagnetic waves 9 using circuit configurations 241 Equivalence of the series and parallel using multiple stubs 122 representations 242 Impedance relations in transmission lines 65, Excess capacitance of a corner 190 77 Impedance values, plotted on Smith chart 92 Feedback amplifiers, design 352 Incident waves 45 FETs 277 Indefinite admittance matrix 316 construction 292 Indirect synthesizers 396 n-channel 277 Inductive stub matching 181 biasing 278 Inductors: properties 290 quality factor 245 Field strength 12 series and parallel forms 245 Field-effect transistors see FETs Input admittance 302 Filter design 203 Input impedance 168 Filters 203 Input impedance of line, verified using PUFF Butterworth filter 208 software 174 normalised parameters 210 Input impedance of low loss transmission lines specification of 206 79 Tchebyscheff filter 225 Input reflection coefficient 323 First order loop 406 Intermediate frequency amplifier with Flip-flop-type phase detector 385 transformers 236 gain sensitivity 385 Isotropic radiation 14 Folded dipole 17 Free-space radiation 11 L matching network 247 Frequency distortion 63 Ladder network 188 Frequency modulation 6 Line impedance derivation 55 Frequency synthesisers 393 Line impedances, found using Smith charts 107 Index 427 Linvill stability factor 304 radio frequency oscillators 368 Lock in range 392 sine wave type oscillators 358 Loop gain, phase lock loops 389 voltage-controlled oscillator 375, 387 Low frequency sine wave oscillators 361 Wein bridge oscillators 361 Low frequency equivalent circuit of a Output admittance 302 transistor 294 Output impedance matching, verification using Low pass filter: PUFF software 185 design 211 Output reflection coefficient 322 using microstrip lines 213 Oven controlled crystal oscillator 379 Mason’s non-touching loop rule 406 Parallel circuits 200 Matched transmission lines 64 Parallel wire line 49 Maximum available gain 307, 321 p-channel 281 Microstrip lines 48, 165 Phase detector 381 as band pass filters 221 types 383 as low pass filters 213 Phase lock loops 380 characteristic impedance 51 Phase modulation 8 step change in width 191 Phase shift oscillators 364 Microwave amplifiers 320 Phase velocities, 63 Microwave CAD packages 407 p network 253 Microwave calculator 412 p -equivalent circuit 293 Microwave path calculations 412 Pin attenuator and switch design 412 MIMP 418 Polar diagram 15 Mismatched loss 69 Polarisation 12 Mismatching techniques 314 Power density 13 Mixer spurious search 411 Pre-scaling 396 MOSFETs 284 Primary line constants 54 biasing 286 Propagation constant in terms of the primary depletion mode MOSFETS 288 constants 72 n-channel enhancement mode type 284 Propagation constant of transmission lines 72 p-channel enhancement-mode type 285 Propagation delay 61 properties 290 Propagation of energy 45 Multi-loop antennas 19 Propagation time delay, in transmission systems Neper 62 Propagation velocity, in transmission systems Network impedances, verification using PUFF 46 software 173 PUFF 2.1 software 43, 142, 198, 330, 417, Noise calculations 412 418 Noise figure 37 bandpass filters 152 nth order loop 406 commands 156 evaluating couplers 170 Operating point, transistors 266 installation 143 Oscillators 357 printing and fabrication of artwork 150, 154 Colpitts oscillator 368 running PUFF 144 comparison of types 376 Smith chart expansion 149 crystal control oscillators 376 s-parameter calculation 186 frequency synthesisers 393 templates 157 Hartley oscillator 371 modification of transistor templates 164 low frequency sine wave oscillators 361 verification of Smith chart applications phase lock loops 380 172 phase shift oscillators 364 Pulse propagation 61 428 Index Quality factor (Q): of detector 403 capacitors 242 of generator 403 inductors 245 of lossless transmission line 402 on Smith charts 93 of series impedance 403 Quarter wave transformers, verification using *of shunt admittance 403 PUFF software 175 Signal propagation on transmission lines 61 Signal to noise ratio 36 Radiating resistance 15 Simultaneous conjugate matching 308 Radio frequency amplifiers 297 Sine wave type oscillators 358 Radio frequency design conditions 304 Single loop antennas 19 Radio frequency oscillators 368 Slot line 48 Radio frequency power transistor 355 Smith charts 88 Radio frequency transistor modelling 297 admittance manipulation 98 Radio receivers 32 applications properties 33 expansion 149 Rat race coupler 85, 170 immitance 97 impedance manipulation 94 Reactances using transmission lines 80 impedance matching 110 Reflected waves in transmission lines 46 impedance networks 104 Reflection coefficient 46, 64, 70, 105, 166 impedance of distributed networks 106 Reflections in transmission systems 46 impedance-to-admittance conversion 95 Return loss 75 plotting impedance values 92 Ring coupler 85 PUFF 2.1 software 149 Q values 94 s parameters see Scattering parameters reflection coefficients 102 SC cut 377 theory and applications 99 Scattering coefficients 401 using PUFF 172 Scattering parameters 125, 186, 321, 401 Spiral inductor design 412 calculation using PUFF 186 Stability circles 339 conversion between s-parameters and Stability of tyransistor 304 y-parameters 131 Standing wave ratio 47 examples in two-port networks 131 Static phase error, phase lock loops 389 in terms of impedances 130 Stern stability factor 306 in transistor amplifier design 321 Strip line 48 incident and reflected waves 127 Stub matching, verification using PUFF Schottky detector calculations 412 software 176, 185 Second channel interference 40 Superheterodyne receiver 38 Second order loop 406 Selectivity 34 T network 257 Sensitivity 36 Tchebyscheff filter 225 Series circuits 197 design procedures 228 Series connected L networks for lower Q Tchebyscheff high pass filter 230 applications 260 Tchebyscheff low pass filter 228 Series elements 187 Tchebyscheff tables 227 Shunt elements 187 Temperature compensated crystal oscillator 379 Signal flow applications 407 Templates, PUFF software 157 Signal flow graph: Thermal analysis 413 analysis, 400 Third order loop 406 *topological manipulation 403 Three element matching networks 252 Signal flow representation: Topological manipulation of signal flow graphs of termination 402 403 Index 429 Transducer gain 311, 329 Tuned circuits 196 PUFF software results 330 cascading 201 Transformer matching 233 Twin lines 49 Transistor action 263 Twin parallel wire characteristic impedance 51 Transistor bias circuits 412 Two-port circuit analysis 412 Transistor biasing 266 Two-port networks 295 Transistor design data 411 Two-way splitter 30 Transistor impedances, matching 181 Transistor operating configurations 316 Unbalanced antennas 25 Transistor stability 320, 321 Unbalanced line 26 Transistor template modification, PUFF Unilateralization and neutralisation 313 software 157 Unmatched transmission lines 64 AC equivalent circuits 291 Vertical rod antennas 18 as a two port network 295 Voltage controlled oscillator 375, 387 high-frequency transistor amplifiers 262 Voltage feedback bias circuit 267, 270 low-frequency equivalent circuit 294 Voltage gain 299 Translation loop, 398 Voltage reflection coefficient 65 Transmission coefficient 46, 64, 69 VSWR 64, 69 Transmission line couplers 82 Transmission lines 412 Wave impedance 12 as transformers 81 Waveguide 45, 47 as electrical components 77 Wein bridge oscillators 361 matched 64 unmatched 64 Yagi-Uda array 23 Transmission path, energy 45 TRF receivers 36 Z0 by measurement 59
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October 2 A teacher gave a test to a class in which 10% of the students are juniors and 90% are seniors. The average score on the test was 84. The juniors all received the same score, and the average score of the seniors was 83. What score did each of the juniors receive on the test? Interactive version of problem and solution. Buy Origami, Eleusis, and the Soma Cube
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General Maths @ Coburg The idea of correlation In analysing the scatterplot we look for a pattern in the way the points lie. Certain patterns tell us that certain relationships exist between the two variables. This is referred to as a correlation Bob and Jim work for the same company. Bob drives a Porsche, costing $200000, and Jim drives an Austin Allegro, costing $9000. Which man has the greater salary? In this case, we can reasonably assume that it must be Bob who earns more, as he drives the more expensive car. As he earns a larger salary, the chances are that he can afford a more expensive car. We can’t be absolutely certain, of course. It could be that Bob’s Porsche was a gift from a friend, or part of the divorce settlement from his wife – or he could have stolen it! However, most of the time, an expensive car means a larger salary. So we say that there is a correlation between someone’s salary and the cost of the car that he/she drives. This means that as one figure change, we can expect the other to change in a fairly regular q-correlation coefficient The q-correlation coefficient is a measure of the strength of the association between two variables. The calculation of the q-correlation coefficient aids us considerably in making that judgment. To calculate the q-correlation coefficient: The value of the q-correlation coefficient in the above example indicates a strong correlation. The diagram below gives a rough guide to the strength of the correlation suggested by the value of q. Practice Questions Question 1 Question 2 a. Calculate the q-correlation coefficient for your scatter plot of height vs arm span. b. Write down what type of relationship exists between the pair of variables and comment on this relationship.
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Math Help April 20th 2011, 10:26 AM #1 Nov 2010 Let f (xy) =f(x) f(y) for every x, y belongs to R.if f(x) is continuous at any one point x=a, then prove that f(x) is continuous for all x belongs to R-{0}. F(x) = 3 if x=0 and [(1+ax+bx^3)/(x^2)]^(1/x) if x is not equal to zero Find a, b if F(x) is continuous at 0.(looks wrong question ) Let f (xy) =f(x) f(y) for every x, y belongs to R.if f(x) is continuous at any one point x=a, then prove that f(x) is continuous for all x belongs to R-{0}. F(x) = 3 if x=0 and [(1+ax+bx^3)/(x^2)]^(1/x) if x is not equal to zero Find a, b if F(x) is continuous at 0.(looks wrong question ) How about showing some work?! For Q1, you could write out what it means for f to be continuous on the given set. That's what they call "beginning with the end in mind". Use the given information about a, have a creative (or logical) insight, and string it all together! I assume that f(xy) means f(x,y), that is to say, the function is not of the product of x and y, but rather it is a function of x and y separately. If that's true then this first part should be false by taking y/(x-1). It will be continuous, say, at x = 2 but discontinuous at x = 1, which is in R-{0}. Perhaps you've made a mistake typing in the statement of the question. I assume that f(xy) means f(x,y), that is to say, the function is not of the product of x and y, but rather it is a function of x and y separately. If that's true then this first part should be false by taking y/(x-1). It will be continuous, say, at x = 2 but discontinuous at x = 1, which is in R-{0}. Perhaps you've made a mistake typing in the statement of the question. Perhaps you have made a mistake in the interpretation of the question! Since the function is defined on R (NOT RxR), xy is a product. NO question is correctly typed. If f is continuous at any (non-zero) a, then, for any x and b, let x= by/a y= bx/a. The f(x)= f(by/a)= f(b/a)f(y). In particular, [tex]\lim_{x\to b}f(x)= \lim_{y\to a} f(by/a)= f(b/a)\lim_{y\to a} f(y)= f(b/a)f(a)= f((b/a)(a))= f(b) However, I believe that $ae 0$ is necessary for this. April 20th 2011, 10:41 AM #2 April 20th 2011, 10:42 AM #3 Jun 2010 April 20th 2011, 10:43 AM #4 April 20th 2011, 10:44 AM #5 Nov 2010 April 20th 2011, 01:36 PM #6 MHF Contributor Apr 2005
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[FOM] Mathematical explanation Richard Heck rgheck at brown.edu Fri Oct 28 16:48:35 EDT 2005 mjmurphy wrote: >On Mon, 24 Oct 2005, I wrote: >>... there is an example of Searle's (borrowed from Wittgenstein, but I don't quite know where). The example involves the mathematical proposition 3 + 4. >Neil said: That's not a proposition, but let's not bother ... >Actually, lets, as it may make Searle's point clearer. [snip] Searle then asks: are there any types of sentence which are immune from this kind of context dependence, and considers mathematical statements in this light: >"Perhaps one might show, for example, that an arithmetical sentence such as "3+4=7" is not dependent on any contextual assumptions for the applicability of its literal meaning. Even here, however, it appears that certain assumptions about the nature of mathematical operations such as addition must be made in order to apply the literal meaning of the sentence." What kinds of assumptions about addition are we supposed to have to make? The example mentioned is one in which there are three nuts in one circle and four in another, but the circles overlap. So what Searle is suggesting is that you can't `apply' "3+4+7" in such a situation. That's obviously true, if what that is supposed to mean is that you shouldn't conclude that there are seven nuts in the union of the circles. But "3+4=7" does not say anything about nuts and circles. (That was Neil's point.) What it implies, and what one can prove logically, is that, if there are three Fs and there are four Gs, and no F is a G, then there are seven F-or-Gs. That has no "conditions of applicability", so far as I can see. And if you're tempted to say it's useless if there are Fs that are G, don't forget you can reason by modus tollens: If you find there aren't seven F-or-Gs, and you know there are three Fs and four Gs, then you can conclude that some F is G. (Frege was rather fond of this sort of point.) >So, to the question "Is mathematics necessary?" It seems to me that if an arithmetical sentence with its literal meaning can be applied under differing assumptions about the nature of mathematical operations, than we have a counter[example] to its application under any particular set of assumptions, and so mathematics is not necessary. No such example could serve to undermine the necessity of mathematical claims. To think that it could is to misunderstand both what context-dependence is and what Searle is arguing: Searle is arguing that the literal meaning of most (or all) sentences underdetermines the propositions expressed by utterances of them, which are determined only contextually. What Murphy says is that "the literal utterance of a statement does not supply us with a proposition which can be used to assess its truth value without reference to context". That comment is ambiguous, and I'll guess that the ambiguity is part of the trouble. What Searle is saying is not that the *assessment* is relative to context (Searle isn't a relativist) but that what proposition is expressed is relative to context. If so, however, then the literal meaning of a sentence is not, in general, truth-evaluable, so of course its literal meaning isn't necessary. But that's trivial. Compare: The proposition expressed by the sentence "I am Richard Heck" is necessarily true if I utter it, but necessarily false if anyone else does. The *sentence* is neither necessary nor contingent, since it isn't truth-evaluable, and the same goes for its literal meaning. Searle is claiming that all sentences are kind of like "I am Richard Heck", but he really thinks they are more like "That is Richard Heck", about which similar things could be said. That mathematical claims are necessary is a thesis about the propositions those claims express. It would be silly to think that the sentence "3+4=7" could not have expressed a falsehood, though that is sometimes said, sloppily. It could have, and it would have had "3" meant what "2" does. Similarly, if there were certain contexts in which utterances of "3+4=7", that would not show that what it expressed in certain other contexts was not necessary. So to argue is seriously confused. Richard Heck Richard G Heck, Jr Professor of Philosophy Brown University Get my public key from http://sks.keyserver.penguin.de Hash: 0x1DE91F1E66FFBDEC Learn how to sign your email using Thunderbird and GnuPG at: More information about the FOM mailing list
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Curriculum and Program Information Hours and Location Mon - Fri:8:30am - 5:00pm Grace Jacobs, 6th Floor • Curriculum and Program Information Curriculum and Program Information Department of Mathematics and Computer Science The Department of Mathematics and Computer Science offers a major and a minor in both Mathematics and Computer Science. Within the Mathematics major the student may choose a concentration in Mathematics Secondary Education. The Mathematics major is intended to prepare students for any of the following: • the study of mathematics on the graduate level • employment in business, government, or industry • teaching mathematics at the secondary level • study in subject areas requiring a strong mathematics background, such as chemistry, economics, engineering, operations research, and actuarial science. The Computer Science major is intended to provide students with the knowledge, aptitudes, and skills required for successful employment in computer-related fields and for the study of computer science on the graduate level. General Education Requirement in Mathematics The General Education Requirements of the University include three semester credit hours in mathematics, excluding credits earned for courses with the DVMT code. Each entering student is required to take a mathematics placement exam. The student's achievement level on this exam and high school mathematics record are used to place the student in DVMT 108, DVMT 109, or a course to satisfy the General Education Requirement. Usually this is one of the following courses, depending on the student's major: MATH 103 Mathematics for Elementary Teachers I MATH 110 College Algebra MATH 125 Mathematics for Liberal Arts MATH 131 College Algebra for Mathematics and Science Majors MATH 203 Basic Statistics The student should consult his/her academic advisor to determine which course to take to satisfy the General Education Requirement in mathematics. The following table summarizes these departmental Mathematics General Education Requirement by Major/Department Department Requirement Applied Psychology MATH 125 Criminal Justice MATH 125 or MATH 203 Education MATH 103 History MATH 125 Humanities and Media MATH 125 Liberal Arts MATH 125 or MATH 203 (or any other MATH course) Management Science MATH 131 Math/Computer Science MATH 131 Natural Science MATH 131 Nursing MATH 110 Social Sciences MATH 125 Social Work MATH 203 Sports Management MATH 125 (except MATH 110 for Sports Medicine concentration) Urban Arts Production MATH 125 or MATH 203 or MATH 203 Course Prerequisites For courses in mathematics and computer science, prerequisites are specified. It is department policy that these prerequisites must be completed with a grade of C or better. Assessment of Majors The extent to which students majoring in both Mathematics (Liberal Arts) and Computer Science have met the goals of the program will be measured before each student graduates. Each student will be required to take a capstone course (MATH 417 or COSC 417 ) in the senior year. The course is intended to cover current and advanced topics in Mathematics (or Computer Science). It will draw together all of the material the students have encountered in their earlier training. The assessment will involve either a project undertaken by a student or group of students and/or a test developed by members of the Mathematics and Computer Science department to measure knowledge of topics taught in the major-requirement courses. Both the project and the test may involve Related items
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Robert Recorde From Wikipedia, the free encyclopedia Robert Recorde (c. 1510 – 1558) was a Welsh physician and mathematician. He introduced the "equals" sign (=) in 1557. A member of a respectable family of Tenby, Wales, he entered the University of Oxford in about 1525, and was elected a fellow of All Souls College in 1531. Having adopted medicine as a profession, he went to the University of Cambridge to take the degree of M.D. in 1545. He afterwards returned to Oxford, where he publicly taught mathematics, as he had done prior to going to Cambridge. It appears that he afterwards went to London, and acted as physician to King Edward VI and to Queen Mary, to whom some of his books are dedicated. He was also controller of the Royal Mint and served as "Comptroller of Mines and Monies" in Ireland.^[1] After being sued for defamation by a political enemy, he was arrested for debt and died in the King's Bench Prison, Southwark, in 1558. Recorde published several works upon mathematical subjects, chiefly in the form of dialogue between master and scholar, such as the following: • The Grounde of Artes, teachings the Worke and Practise, of Arithmeticke, both in whole numbers and fractions (c. 1540), the first English book on algebra. • The Pathway to Knowledge, containing the First Principles of Geometry ... bothe for the use of Instrumentes Geometricall and Astronomicall, and also for Projection of Plattes (London, 1551) • The Castle of Knowledge, containing the Explication of the Sphere both Celestiall and Materiall, etc. (London, 1556) • The Whetstone of Witte, whiche is the seconde parte of Arithmeteke: containing the extraction of rootes; the cossike practise, with the rule of equation; and the workes of Surde Nombers (London, 1557). This was the book in which the equals sign was introduced. With the publication of this book Recorde is credited with introducing algebra into England.^[2] • a medical work, The Urinal of Physic (1548), frequently reprinted. Sherburne states that Recorde also published Cosmographiae isagoge, and that he wrote a book De Arte faciendi Horologium and another De Usu Globorum et de Statu temporum. Recorde's chief contributions to the progress of algebra were in the way of systematizing its notation. See also 1. ^ Newman, James R. 1956, "The World Of Mathematics" 2. ^ Jourdain, Philip E. B. 1913, "The Nature Of Mathematics" • This article incorporates text from the article "Robert Recorde" in the Encyclopædia Britannica, Eleventh Edition, a publication now in the public domain. • Newman, James R. (1956), "The World Of Mathematics" Vol. 1 "Commentary On Robert Recorde" • Jourdain, Philip E.B. (1913), "The Nature Of Mathematics" External links
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Math Forum Discussions Math Forum Ask Dr. Math Internet Newsletter Teacher Exchange Search All of the Math Forum: Views expressed in these public forums are not endorsed by Drexel University or The Math Forum. Topic: Who cares the null hypotheses (two-tail test) is really TRUE? Replies: 2 Last Post: Dec 22, 2012 7:42 PM Messages: [ Previous | Next ] Luis A. Re: Who cares the null hypotheses (two-tail test) is really TRUE? Afonso Posted: Dec 22, 2012 7:42 PM Posts: Comment about From: ?Should Psychology abandon p-values and teach CI´s instead? Evidence-based reform in Statistics education?. LIsbon Fiona Fidler (2006). (Portugal) www.stat.auckland.ac.nz/~iase/publications/17/5E4_FIDL.pdf - 2/16/05 I, myself, never search if a hypothesis is true or false . . . a chimerical goal I do not pursue. We should not care, at all, such a thing: is impossible and uninteresting. What we are only able to achieve is if there is (or not) sufficient evidence/plausibility to reject the Null Hypothesis giving the data. To bring the Aristotelian logic (true/false) to events subjected to chance is plainly erroneous. The A. said, all people agree: ?particularly serious misconception associated with NHST, namely that statistical non-significance is equivalent of evidence of `no effect`. But immediately she state that ? from a low power study with a no-trivial effect size - as evidence the null hypotheses is true . . . suggest that she have the concern, about she criticise as a method?s weakness: a sufficiently large sample will invalidate this result. But this is expected, of course, this is natural: even a little difference will be evident from data, therefore leading to H0 rejection. A difference that could be, evidently, insignificant for practical purposes. Luis A. Afonso Date Subject Author 8/5/11 Who cares the null hypotheses (two-tail test) is really TRUE? Luis A. Afonso 8/6/11 You NEVER know if a coin is FAIR! Luis A. Afonso 12/22/12 Re: Who cares the null hypotheses (two-tail test) is really TRUE? Luis A. Afonso
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Crystal Growth in a Computer U, potential energy or chemical binding energy; k[b], Boltzmann's constant or 1.38041x10-23 T, absolute Temperature (Kelvin) where the temperature for the triple point of water is 273.15 Kelvin. The study of the growth of solid crystals, whether in a liquid solution or by vapor deposition in a vacuum chamber, is an important and intriguing process. It is a process which has many important uses in such industries as pharmaceuticals to semiconductors. The process for this project is simple. We start with a seed crystal or substrate with which atoms from the solution or vapor collide. Some of these atoms become a part of the crystal and the substrate grows. Many students have studied the growth of sugar crystals on a string placed in a supersaturated solution of sugar-water. A process of great importance today is the growth of near perfect crystals for the semiconductor industry. The computer industry is interested only in those processes which may consistently produce a well ordered crystalline solid, free of defects or vacancies. Amorphous solids, unstructured groups of atoms, are rejected. The production of crystals are determined by factors such as the quality and temperature of the seed crystal and the rate of growth. We begin with a substrate of atoms, the seed crystal, and randomly drop atoms onto the substrate. Three things happen: 1. the atom sticks at that site 2. the atom bounces off the substrate completely 3. the atom may move to a neighboring position on the surface of the substrate The outcome is determined by the temperature and the potential (chemical binding) energy U of the atom on the surface of the substrate. Boltzmanns factor e^(-U/kbT) determines the probability of sticking. Qualitatively we would expect the crystals to develop differently at different temperatures, at low temperatures the atoms tend to stick to the substrate and at high temperatures the atoms' thermal energy allow them to bounce off the substrate. Figure 1. At location [i,j], there are eight neighbors. The atom at [i,j] would have two types of bonds: a bond with a neighbor in the same row or column is a perpendicular bond, while the bonds with the four remaining neighbors are called diagonal bonds. This procedure is accomplished for each of the four perpendicular neighbors of the site, top, right, bottom, and left. (Here, let j=1 be our present position, j=2: top, j=3:right, j=4:bottom, j= 5:1eft). The five values of the PE's are summed to calculate a total potential energy for that site, PETOTAL. Now for each of the five sites a probability factor is calculated by dividing the individual energy values by the total: PROBj=PEj/PETOTAL. Next the simulation calculates a random number between zero and one, RAND, against which we will compare the probability of current position: 1. if ProB 1 >= RAND we record a 1 at location [i,j] and the "clock" value at time[i,j]; 2. else if PROB 1 + PROB2 > RAND let [i,j+l], the top, be our current position and go tbrough the whole process again; 3. else if PROB 1 + PROB2 + PROB3 > RAND let [i+l,j], the right, be our current position and go through the whole process again; 4. else if PROB l+PROB2+PROB3+PROB4>RAND let [i,j-l ], the bottom, be our current position and go through the whole process again; 5. else let [i-1,j], the left, be our current position. This process gives the atom the ability to jump to different sites and calculate whether the atom might stick at a site which borders the selected site. The procedures exist if: • ST = 0 and DI = O (there are no neighbors) • the column chosen is either the first or last colutnn, or the row selected is at the top of the grid definition, the top row. Whether or not the atom sticks, the programs should increment the 'clock' and go on to find the next random column. The clock for this program will be an interation count through the routine. The clock will be initialized to zero at the beginning of the program. The time required to fill up the grid with crystals depends on the Boltzmann temperature constant and tbe bonding strengths. For a 75x30 grid a thousand clock cycles should be sufficient. Due to system and time constraints only results from some of the clock cycles will be saved. The user will determine which clock cycles to save. In order for the user to choose, they should be prompted for: 1. the name of the output file 2. the minimum clock value at which to start saving the data 3. the maximum clock value at which time the algorithm terminates 4. the number of clock cycles skipped to the next data saved, this is done by using the Pascal modulus operator, 'mod' Main program: initialize; {call the initialize procedure} get_parameters; {call the procedure which asks the user for the constant values} loop: while clock <= maximum time {get a random column and find the row just above the monte_carlo(thiscolumn, thisrow); {pass the column and row of the algorithm} if: the time checks are correct output the data in AVS format; increment clock; clock = 0; all the entries for location[i,j] will be zero except for the bottom row, location[i, 1] will Get parameters: prompt user for the parameters kbT, diagonal bond strength, perpendicular bond strength, minimum and maximum clock cycles, and the number of clock cycles to skip before saving the data, and the name of the output file. Random Column: get a random integer value between 1 and the maximum column; drop from the top to the bottom to find the row just above the substrate below, this includes the diagonal neghbors, also; Monte Carlo procedure: we need the arrays of reals: BP[1..5], PE[1..5], PROB[1..5] Sticking calculation procedure (i, j, k): if location [i, j] = 1 BP[k] = PE[k] = 0.0; calculate the number of diagonal neighbors and perpendicular neighbors; calculate BP[k], PE[k] and PETOTAL as discussed earlier; [it is important to keep in mind that not every location has eight neighbors] initialize BP[ ] and PE [ ] to zero; call sticking (this column, thisrow, neighborlocation); if there are no neighbors exit routine; else if the column is the last or first column or the top row pass the up (neighbor location = 2), right (nl=3), bottom (nl = 4), and left (nl = 5) column, row, and "nl" values to sticking procedure. calculate a random value, RAND, between 0 and 1; check the random comparisons as discussed earlier, updating the crystal information when necessary otherwise allow the atom to jump to its perpendicular Output procedure: for each time iteration saved, there are two output files - an AVS header file and the data file. With the flexibility of the user prompted parameters we may investigate the various properties of the crystal growth process. Figures 2 & 3 show some of the different crystals which develop under different conditions. Figure 2. kT=28, diagonal bond = 100, perpendicular bond =10 Figure 3. kT=5, diagonal bond=100, perpendicular bond=10 SI 1998 This code was developed from a simulation developed by Berkowitz, S.J., and Haase, D.G., and was originally written in BASICA for the IBM PC. Leslie Southern is the OSC coordinator for the Crystal Growth project. Leslie's office is in 420-3. Please contact Leslie to set up appointment(s) for consultation. For assistance, write si-contact@osc.edu or call 614-292-0890.
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What's the Division Property of Equality? Ever wondered what rules you're allowed to follow when you're working with inequalities? Well, one of those rules is called the division property of inequality, and it basically says that if you divide one side of an inequality by a number, you can divide the other side of the inequality by the same number. However, you have to be very careful about the direction of the inequality! Watch the tutorial to see how this looks in terms of algebra!
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basic linear algebra questions April 17th 2009, 07:32 PM Hikari Clover basic linear algebra questions let ABC be a triangle and let p be the midpoint of side AB let http://i52.photobucket.com/albums/g37/mmmmms/1-7.jpg and http://i52.photobucket.com/albums/g37/mmmmms/2-6.jpg express http://i52.photobucket.com/albums/g37/mmmmms/5-3.jpg and http://i52.photobucket.com/albums/g37/mmmmms/6-2.jpg in terms of http://i52.photobucket.com/albums/g37/mmmmms/7-1.jpg and http:// i52.photobucket.com/albums/g37/mmmmms/8-1.jpg and http://i52.photobucket.com/albums/g37/mmmmms/9-1.jpg hence prove that the midpoint of the hypotenuse of a right-angle triangle is equidistant from the three vertices let p be the plane with cartesian equation 2x+y-3z=9 and let A,B be points with coordinates (1,-2,3) and (-2,1,-1) l is the line passing through the point A and B find the coordinates of the point C where the line l intersects the plane p i have no ideas how to find the intersection between a line and a plane April 17th 2009, 11:43 PM let ABC be a triangle and let p be the midpoint of side AB let http://i52.photobucket.com/albums/g37/mmmmms/1-7.jpg and http://i52.photobucket.com/albums/g37/mmmmms/2-6.jpg express http://i52.photobucket.com/albums/g37/mmmmms/5-3.jpg and http://i52.photobucket.com/albums/g37/mmmmms/6-2.jpg in terms of http://i52.photobucket.com/albums/g37/mmmmms/7-1.jpg and http:// i52.photobucket.com/albums/g37/mmmmms/8-1.jpg and http://i52.photobucket.com/albums/g37/mmmmms/9-1.jpg hence prove that the midpoint of the hypotenuse of a right-angle triangle is equidistant from the three vertices $\overrightarrow{AP}^2 = \frac12\:\overrightarrow{AB}\cdot\frac12\:\overrig htarrow{AB}\cdot = \frac14\:\overrightarrow{AB}\cdot\overrightarrow{A B}$ $\overrightarrow{AB} = \overrightarrow{AC} + \overrightarrow{CB} = -\vec{a} + \vec{b}$ $\overrightarrow{AP}^2 = \frac14\:\left(-\vec{a} + \vec{b})^2\right) = \frac14\:\left(\vec{a}^2 + \vec{b}^2 -2 \vec{a} \cdot \vec{b}\right)$ $\overrightarrow{CP} = \frac12\:\left(\overrightarrow{CA} + \overrightarrow{CB}\right) = \frac12\:\left(\vec{a} + \vec{b}\right)$ let p be the plane with cartesian equation 2x+y-3z=9 and let A,B be points with coordinates (1,-2,3) and (-2,1,-1) l is the line passing through the point A and B find the coordinates of the point C where the line l intersects the plane p i have no ideas how to find the intersection between a line and a plane AB coordinates are (-3,3,-4) Therefore one parametric equation of l is : x = -3t + 1 y = 3t -2 z = -4t +3 C(x,y,z) is on the plane iff 2x+y-3z=9 C is on l iff there exists t such that x = -3t + 1 y = 3t -2 z = -4t +3 Substitute x,y,z in the Cartesian equation of the plane to get one linear equation. Solve for t and substitute in x,y,z expressions. April 18th 2009, 04:20 AM Hikari Clover $\overrightarrow{AP}^2 = \frac12\:\overrightarrow{AB}\cdot\frac12\:\overrig htarrow{AB}\cdot = \frac14\:\overrightarrow{AB}\cdot\overrightarrow{A B}$ $\overrightarrow{AB} = \overrightarrow{AC} + \overrightarrow{CB} = -\vec{a} + \vec{b}$ $\overrightarrow{AP}^2 = \frac14\:\left(-\vec{a} + \vec{b})^2\right) = \frac14\:\left(\vec{a}^2 + \vec{b}^2 -2 \vec{a} \cdot \vec{b}\right)$ $\overrightarrow{CP} = \frac12\:\left(\overrightarrow{CA} + \overrightarrow{CB}\right) = \frac12\:\left(\vec{a} + \vec{b}\right)$ AB coordinates are (-3,3,-4) Therefore one parametric equation of l is : x = -3t + 1 y = 3t -2 z = -4t +3 C(x,y,z) is on the plane iff 2x+y-3z=9 C is on l iff there exists t such that x = -3t + 1 y = 3t -2 z = -4t +3 Substitute x,y,z in the Cartesian equation of the plane to get one linear equation. Solve for t and substitute in x,y,z expressions. hey , thx for ur replying(Clapping) but for the first question,did u forget to put that absolute value sign? or it doesnot matter? April 18th 2009, 05:58 AM Are you talking about the modulus ? $||\overrightarrow{AB}||^2 = \overrightarrow{AB}\cdot\overrightarrow{AB} = \overrightarrow{AB}^2 = AB^2$ April 18th 2009, 06:17 AM Hikari Clover oh i got it thanks so much ^_^
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Miramar, FL Calculus Tutor Find a Miramar, FL Calculus Tutor ...I have taken two college level courses in C++, and have completed many C++ projects for clients on a freelance basis. I am a mathematics major at FIU and took Linear Algebra in Fall 2011. I have taken classes in Formal (Philosophical) Logic, Mathematical Logic, Set Theory, and other branches of Logic. 27 Subjects: including calculus, English, reading, algebra 1 ...I earned a Bachelor's Degree in Mechanical Engineering plus a Master's Degree in Aircraft Engineering and a Bachelor's plus an MBA in International Business with 327 credit hours in undergraduate and graduate courses. As a high-school student, I qualified and participated to the National Math Ol... 22 Subjects: including calculus, physics, geometry, statistics ...My native language is Spanish. For those students that need some help with reading, I can help them too, in English and in Spanish. My experience as a customer service person permits me to treat the persons with the golden rule: "Treat other people the way you you would like to be treated." Di... 14 Subjects: including calculus, English, Spanish, chemistry ...Step-by-step learning is the secret of my success. I have a solid background in Calculus, Algebra, Geometry, Trigonometry, Physic, Analytic Geometry, Technical and Mechanical Drawing, AutoCAD, Mechanics of Fluids, Thermodynamic, Refrigeration and HVAC, Mechanical Design, and Resistance of Material. I graduated from the Mechanical Engineering school at the Havana University in 1974. 8 Subjects: including calculus, geometry, algebra 2, trigonometry ...I worked for General Tire and Rubber, Ford Motor Co and Visteon Corp a total of 38.5 years. I am currently working for H&R Block and have been teaching the Income Tax Course for 4 years. I taught Statistical Process Control, Quality Control and Process Improvement Courses at Ford Motor Co. 21 Subjects: including calculus, chemistry, algebra 1, Spanish
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help with proof December 1st 2009, 04:13 PM help with proof Prove the following: An accumulation point of a set S is either an interior point of S or a boundary point of S. This seems very logical to me, I just dont know how to prove it. I know that an accumulation point may or may not be in S. If it is in S then it would be an interior and boundary. If it is not in S then it would be a boundary point. Pretty simple I think, but how can I actually prove this? December 1st 2009, 04:57 PM Prove the following: An accumulation point of a set S is either an interior point of S or a boundary point of S. This seems very logical to me, I just dont know how to prove it. I know that an accumulation point may or may not be in S. If it is in S then it would be an interior and boundary. If it is not in S then it would be a boundary point. Pretty simple I think, but how can I actually prove this? Let $E$ be a set and $\xi$ a limit point of $E$. Then for every neighborhood $N_{\varepsilon}(\xi)$ there contains a point of $E$ different from $E$. Note now that if we consider let $P$ be the statement "there exists some neighborhood of $\xi$ such that it is contained in $E$" then "Every neigborhood of $\xi$ contains a point of $E^{c}$" is the statement $eg P$. And since we are working in first order logic it follows that $P\vee eg P$ is a tautology. You get the idea. December 15th 2009, 07:44 PM I have been reading this post for awhile and the way you structured the proof does not make any sense to me. Is there any other way to show this proof? like with if X is in S or if x is not S sort of version then there exists a deleted neighborhood intersected with S that is nonempty? I kind of have the jist of what accumulation points, boundary and interior points are but im having trouble forming a proof in my own words. S is a subset of R. I know that if x is an accumulation point there exists $N*(x, {\varepsilon} ) \cap$ S =/= $\emptyset$. So by that if x is in the deleted neighborhood and an accumulation point (meaning x is in S'), then x is not in S. If x is not in S then x is in R/S. So if x is in R/S then that means that $N(x , \varepsilon) \cap (R/S)$ =/= $\emptyset.$ So x in the bd of S. Is this kind of on the right track? December 15th 2009, 08:25 PM I have been reading this post for awhile and the way you structured the proof does not make any sense to me. Is there any other way to show this proof? like with if X is in S or if x is not S sort of version then there exists a deleted neighborhood intersected with S that is nonempty? I kind of have the jist of what accumulation points, boundary and interior points are but im having trouble forming a proof in my own words. S is a subset of R. I know that if x is an accumulation point there exists $N*(x, {\varepsilon} ) \cap$ S =/= $\emptyset$. So by that if x is in the deleted neighborhood and an accumulation point (meaning x is in S'), then x is not in S. If x is not in S then x is in R/S. So if x is in R/S then that means that $N(x , \varepsilon) \cap (R/S)$ =/= $\emptyset.$ So x in the bd of S. Is this kind of on the right track? I was a little lazy. I think if I rephrase my argument more rigorously it will make more sense. Assume that $\xi\in S'$, then $\forall\varepsilon>0$ there exists some $x\in S,xe\xi$ such that $x\in N_{\varepsilon}(\xi)$. Now if there exists some $\varepsilon'>0$ such that $N_{\varepsilon'} (\xi)\subseteq S$ then $\xi\in S^{\circ}$. If not, then $\forall\varepsilon>0$ it is true that $N_{\varepsilon}(\xi)subseteq S$ which means there exists some point $y\in S^{c}$ such that $y\in N_ {\varepsilon}(\xi)$. Consequently, every neighborhood of $\xi$ contains a point of $S^c$, but since $\xi\in S'$ it is true that every neighborhood also contains a point of $S$. This tells us that $\xi\in\partial S$. $\partial S$-boundary $S'$-limit points December 15th 2009, 08:41 PM I was a little lazy. I think if I rephrase my argument more rigorously it will make more sense. Assume that $\xi\in S'$, then $\forall\varepsilon>0$ there exists some $x\in S,xe\xi$ such that $x\in N_{\varepsilon}(\xi)$. Now if there exists some $\varepsilon'>0$ such that $N_{\varepsilon'} (\xi)\subseteq S$ then $\xi\in S^{\circ}$. If not, then $\forall\varepsilon>0$ it is true that $N_{\varepsilon}(\xi)subseteq S$ which means there exists some point $y\in S^{c}$ such that $y\in N_ {\varepsilon}(\xi)$. Consequently, every neighborhood of $\xi$ contains a point of $S^c$, but since $\xi\in S'$ it is true that every neighborhood also contains a point of $S$. This tells us that $\xi\in\partial S$. $\partial S$-boundary $S'$-limit points Thank you, its kind of late so im really having trouble putting anything of value together but at first glance this makes ALOT more sense.. December 16th 2009, 03:01 AM I would be inclined to use indirect proof: Assume a point, p, is NOT either an interior point or a boundary point of S. Then p is an interior point of the complemennt of S. Prove that s cannot be an accumulation point of S. December 16th 2009, 07:39 AM the second part of the question says: Prove the following: (b)A boundary of a set S is either an accumulation point of S or an isolated point of S. I tried doing it by contradiction but Im not sure you can do this part that way. If I assume a point p is not an accumulation point nor an isolated point, then this point could be an interior point of S, or an interior point of R/S? is that correct? December 16th 2009, 07:57 AM Suppose that $x\in\beta(S)$, the boundary. If $x$ is an isolated point of $S$ we are done. Suppose that it is not. For all open sets $\mathcal{O}$ if $x \in \mathcal{O} \Rightarrow \quad \left( {\exists y \in \mathcal{O} \cap S\backslash \{ x\} } \right)$. What does that tell us? December 16th 2009, 08:11 AM Suppose that $x\in\beta(S)$, the boundary. If $x$ is an isolated point of $S$ we are done. Suppose that it is not. For all open sets $\mathcal{O}$ if $x \in \mathcal{O} \Rightarrow \quad \left( {\exists y \in \mathcal{O} \cap S\backslash \{ x\} } \right)$. What does that tell us? x and y are both in that intersection? December 16th 2009, 08:44 AM Does it mean that every open set that contains $x$ contains a point of $S$ distinct from $x$? What is that the definition of? December 16th 2009, 08:46 AM
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Using Stock Fundamental Analysis to Value a Company By: InvestorGuide Staff, dated January 25th, 2013 Fundamental analysis is a method used to determine the value of a stock by analyzing the financial data that is ‘fundamental’ to the company. That means that fundamental analysis takes into consideration only those variables that are directly related to the company itself, such as its earnings, its dividends, and its sales. Fundamental analysis does not look at the overall state of the market nor does it include behavioral variables in its methodology. It focuses exclusively on the company’s business in order to determine whether or not the stock should be bought or sold. Critics of fundamental analysis often charge that the practice is either irrelevant or that it is inherently flawed. The first group, made up largely of proponents of the efficient market hypothesis, say that fundamental analysis is a useless practice since a stock’s price will always already take into account the company’s financial data . In other words, they argue that it is impossible to learn anything new about a company by analyzing its fundamentals that the market as a whole does not already know, since everyone has access to the same financial information. The other major argument against fundamental analysis is more practical than theoretical. These critics charge that fundamental analysis is too unscientific a process, and that it’s difficult to get a clear picture of a company’s value when there are so many qualitative factors such as a company’s management and its competitive landscape. However, such critics are in the minority. Most individual investors and investment professionals believe that fundamental analysis is useful, either alone or in combination with other techniques. If you decide that fundamental analysis is the method for you, you’ll find that a company’s financial statements (its income statement, its balance sheet and its cash flow statement) will be indispensable resources for your analysis . And even if you’re not totally sold on the idea of fundamental analysis, it’s probably a good idea for you to familiarize yourself with some of the valuation measures it uses since they are often talked about in other types of stock valuation techniques as well. It is often said that earnings are the “bottom line” when it comes to valuing a company’s stock, and indeed fundamental analysis places much emphasis upon a company’s earnings. Simply put, earnings are how much profit (or loss) a company has made after subtracting expenses. During a specific period of time, all public companies are required to report their earnings on a quarterly basis through a 10-Q Report . Earnings are important to investors because they give an indication of the company’s expected dividends and its potential for growth and capital appreciation. That does not necessarily mean, however, that low or negative earnings always indicate a bad stock; for example, many young companies report negative earnings as they attempt to grow quickly enough to capture a new market, at which point they’ll be even more profitable than they otherwise might have been. The key is to look at the data underlying a company’s earnings on its financial statements and to use the following profitability ratios to determine whether or not the stock is a sound investment. Earnings Per Share Comparing total net earnings for various companies is usually not a good idea, since net earnings numbers don’t take into account how many shares of stock are outstanding (in other words, they don’t take into account how many owners you have to divide the earnings among). In order to make earnings comparisons more useful across companies, fundamental analysts instead look at a company’s earnings per share (EPS). EPS is calculated by taking a company’s net earnings and dividing by the number of outstanding shares of stock the company has. For example, if a company reports $10 million in net earnings for the previous year and has 5 million shares of stock outstanding, then that company has an EPS of $2 per share. EPS can be calculated for the previous year (“trailing EPS”), for the current year (“current EPS”), or for the coming year (“forward EPS”). Note that last year’s EPS would be actual, while current year and forward year EPS would be estimates. P/E Ratio EPS is a great way to compare earnings across companies, but it doesn’t tell you anything about how the market values the stock. That’s why fundamental analysts use the price-to-earnings ratio, more commonly known as the P/E ratio, to figure out how much the market is willing to pay for a company’s earnings. You can calculate a stock’s P/E ratio by taking its price per share and dividing by its EPS. For instance, if a stock is priced at $50 per share and it has an EPS of $5 per share, then it has a P/E ratio of 10. (Or equivalently, you could calculate the P/E ratio by dividing the company’s total market cap by the company’s total earnings; this would result in the same number.) P/E can be calculated for the previous year (“trailing P/E”), for the current year (“current P/E”), or for the coming year (“forward P/E”). The higher the P/E, the more the market is willing to pay for each dollar of annual earnings. Note that last year’s P/E would be actual, while current year and forward year P/E would be estimates, but in each case, the “P” in the equation is the current price. Companies that are not currently profitable (that is, ones which have negative earnings) don’t have a P/E ratio at all. For those companies you may want to calculate the price-to-sales ratio (PSR) instead. So is a stock with a high P/E ratio always overvalued? Not necessarily. The stock could have a high P/E ratio because investors are convinced that it will have strong earnings growth in the future and so they bid up the stock’s price now. Fortunately, there is another ratio that you can use that takes into consideration a stock’s projected earnings growth: it’s called the PEG. PEG is calculated by taking a stock’s P/E ratio and dividing by its expected percentage earnings growth for the next year. So, a stock with a P/E ratio of 40 that is expected to grow its earnings by 20% the next year would have a PEG of 2. In general, the lower the PEG, the better the value, because you would be paying less for each unit of earnings growth. Dividend Yield The dividend yield measures what percentage return a company pays out to its shareholders in the form of dividends . It is calculated by taking the amount of dividends paid per share over the course of a year and dividing by the stock’s price. For example, if a stock pays out $2 in dividends over the course of a year and trades at $40, then it has a dividend yield of 5%. Mature, well-established companies tend to have higher dividend yields, while young, growth-oriented companies tend to have lower ones, and most small growing companies don’t have a dividend yield at all because they don’t pay out dividends. Dividend Payout Ratio The dividend payout ratio shows what percentage of a company’s earnings it is paying out to investors in the form of dividends. It is calculated by taking the company’s annual dividends per share and dividing by its annual earnings per share (EPS). So, if a company pays out $1 per share annually in dividends and it has an EPS of $2 for the year, then that company has a dividend payout ratio of 50%; in other words, the company paid out 50% of its earnings in dividends. Companies that distribute dividends typically use about 25% to 50% of their earnings for dividend payments. The higher the payout ratio, the less confidence the company has that it would’ve been able to find better uses for the money it earned. This is not necessarily either good or bad; companies that are still growing will tend to have lower dividend payout ratios than very large companies, because they are more likely to have other productive uses for the earnings. Book Value The book value of a company is the company’s net worth, as measured by its total assets minus its total liabilities. This is how much the company would have left over in assets if it went out of business immediately. Since companies are usually expected to grow and generate more profits in the future, most companies end up being worth far more in the marketplace than their book value would suggest. For this reason, book value is of more interest to value investors than growth investors. In order to compare book values across companies, you should use book value per share, which is simply the company’s last quarterly book value divided by the number of shares of stock it has outstanding. Price / Book A company’s price-to-book ratio (P/B ratio) is determined by taking the company’s per share stock price and dividing by the company’s book value per share. For instance, if a company currently trades at $100 and has a book value per share of $5, then that company has a P/B ratio of 20. The higher the ratio, the higher the premium the market is willing to pay for the company above its hard assets. Price-to-book ratio is of more interest to value investors than growth investors. Price / Sales Ratio As with earnings and book value, you can find out how much the market is valuing a company by comparing the company’s price to its annual sales. This measure is known as the price-to-sales ratio (P/S or PSR). You can calculate the P/S by taking the stock’s current price and dividing by the company’s total sales per share for the past year (or equivalently, by dividing the entire company’s market cap by its total sales). That means that a company whose stock trades at $1 per share and which had $2 per share in sales last year will have a P/S of 0.5. Low P/S ratios (below one) are usually thought to be the better investment since their sales are priced cheaply. However, P/S, like P/E ratios and P/B ratios, are numbers that are subject to much interpretation and debate. Sales obviously don’t reveal the whole picture: a company could be selling dollar bills for 90 cents each, and have huge sales but be terribly unprofitable. Because of the limitations, P/S ratios are usually used only for unprofitable companies, since such companies don’t have a P/E ratio . Return on Equity Return on equity (ROE) shows you how much profit a company generates in comparison to its book value . The ratio is calculated by taking a company’s after-tax income (after preferred stock dividends but before common stock dividends) and dividing by its book value (which is equal to its assets minus its liabilities). It is used as a general indication of the company’s efficiency; in other words, how much profit it is able to generate given the resources provided by its stockholders. Investors usually look for companies with ROEs that are high and growing. Other relevant articles you may like One Response to “Using Stock Fundamental Analysis to Value a Company” 1. Neat summary of stock valuation ratios and measures. Thanks.
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Basic Rules of Algebra There are basic properties in math that apply to all real numbers. When working with variables in algebra, these properties still apply. We will apply most of the following properties to solve various Algebraic problems. Algebraic Properties Let a, b, and c be real numbers, variables, or algebraic expressions. Commutative Property of Addition We can add numbers in any order. Commmutative Property of Multiplication We can also multiply numbers in any order. Associative Property of Addition We can group numbers in a sum any way we want and get the same answer. Associative Property of Multiplication We can group numbers in a product any way we want and get the same answer. Distributive Property When we are adding and multiplying with a parenthesis, we can distribute the multiplication through the addition. For an in depth discussion, see Distributive Property Additive Identity Property If we add 0 to any number, we will end up with the same number. Multiplicative Identity Property If we multiply 1 to any number, we will end up with the same number. Additive Inverse Property If we adda number by the opposite of itself, we will end up with 0. Multiplicative Inverse Property If we multiply a number by its reciprocal, we will end up with 1. Keep in mind that subtraction is also considered addition, but with a negative number. Similarly, divison can be thought of as inverse multiplication, but with a restriction that the denominator cannot be equal to 0. Properties of Negation We must be careful not to make arithmetic mistakes when dealing with negative signs and subtraction. Properties of Equality Add c to each side Multiply both sides by c Subtract c from both sides Divide both sides by c Properties of Zero 0 added or subtracted to anything equals itself 0 multiplied by anything equals 0 0 divided by anything equals 0 We cannot divide by 0 Zero Product Property If the product of two or more things equals 0, at least one of the values must be 0 Properties and Operations of Fractions Let a, b, c and d be real numbers, variables, or algebraic expressions such that b and d do not equal 0. Equivalent Fractions cross multiply Rules of Signs the negative can go anywhere in the fraction and two negatives equal a positive Generate Equivalent Fractions multiplying the top and bottom by the same thing keeps the fraction the same value Add/Subtract with Like Denominators if the denominators are the same, add or subtract the top of the fraction Add/Subtract with Unlike Denominators find a common denominator Multiply Fractions top times the top and bottom times the bottom Divide Fractions when dividing two fracitons, multiply the divisor by the reciprocal Sign up for free to access more algebra 1 resources like . WyzAnt Resources features blogs, videos, lessons, and more about algebra 1 and over 250 other subjects. Stop struggling and start learning today with thousands of free resources!
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Algebra Tutors Santa Clarita, CA 91350 Physics/Math tutor with emphasis in coding and astronomy ...I took I in High School and passed with an A. I continue to tutor and help others with math at a much higher level with heavy involvement in I. I deal with basic and advanced to this day with research. I took II in High School and... Offering 10+ subjects including algebra 1 and algebra 2
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JEE Main The syllabus contains two Sections - A and B. Section - A pertains to the Theory Part having 80% weightage, while Section - B contains Practical Component (Experimental Skills) having 20% weightage. SECTION – A Physics, technology and society, S I units, Fundamental and derived units. Least count, accuracy and precision of measuring instruments, Errors in measurement, Dimensions of Physical quantities, dimensional analysis and its applications. UNIT 2: KINEMATICS Frame of reference. Motion in a straight line: Position-time graph, speed and velocity. Uniform and non-uniform motion, average speed and instantaneous velocity Uniformly accelerated motion, velocity-time, position-time graphs, relations for uniformly accelerated motion. Scalars and Vectors, Vector addition and Subtraction, Zero Vector, Scalar and Vector products, Unit Vector, Resolution of a Vector. Relative Velocity, Motion in a plane, Projectile Motion, Uniform Circular Motion. UNIT 3: LAWS OF MOTION Force and Inertia, Newton’s First Law of motion; Momentum, Newton’s Second Law of motion; Impulse; Newton’s Third Law of motion. Law of conservation of linear momentum and its applications, Equilibrium of concurrent forces. Static and Kinetic friction, laws of friction, rolling friction. Dynamics of uniform circular motion: Centripetal force and its applications. UNIT 4: WORK, ENERGY AND POWER Work done by a constant force and a variable force; kinetic and potential energies, workenergy theorem, power. Potential energy of a spring, conservation of mechanical energy, conservative and nonconservative forces; Elastic and inelastic collisions in one and two dimensions. Centre of mass of a two-particle system, Centre of mass of a rigid body; Basic concepts of rotational motion; moment of a force, torque, angular momentum, conservation of angular momentum and its applications; moment of inertia, radius of gyration. Values of moments of inertia for simple geometrical objects, parallel and perpendicular axes theorems and their applications. Rigid body rotation, equations of rotational motion. UNIT 6: GRAVITATION The universal law of gravitation. Acceleration due to gravity and its variation with altitude and depth. Kepler’s laws of planetary motion. Gravitational potential energy; gravitational potential. Escape velocity. Orbital velocity of a satellite. Geo-stationary satellites. Elastic behaviour, Stress-strain relationship, Hooke’s Law, Young’s modulus, bulk modulus, modulus of rigidity. Pressure due to a fluid column; Pascal’s law and its applications. Viscosity, Stokes’ law, terminal velocity, streamline and turbulent flow, Reynolds number. Bernoulli’s principle and its applications. Surface energy and surface tension, angle of contact, application of surface tension - drops, bubbles and capillary rise. Heat, temperature, thermal expansion; specific heat capacity, calorimetry; change of state, latent heat. Heat transfer-conduction, convection and radiation, Newton’s law of cooling. Thermal equilibrium, zeroth law of thermodynamics, concept of temperature. Heat, work and internal energy. First law of thermodynamics. Second law of thermodynamics: reversible and irreversible processes. Carnot engine and its efficiency. UNIT 9: KINETIC THEORY OF GASES Equation of state of a perfect gas, work doneon compressing a gas.Kinetic theory of gases - assumptions, concept of pressure. Kinetic energy and temperature: rms speed of gas molecules; Degrees of freedom, Law of equipartition of energy,applications to specific heat capacities of gases; Mean free path, Avogadro’s number. UNIT 10: OSCILLATIONS AND WAVES Periodic motion - period, frequency, displacement as a function of time. Periodic functions. Simple harmonic motion (S.H.M.) and its equation; phase; oscillations of a spring -restoring force and force constant; energy in S.H.M. - kinetic and potential energies; Simple pendulum - derivation of expression for its time period; Free, forced and damped oscillations, resonance. Wave motion. Longitudinal and transverse waves, speed of a wave. Displacement relation for a progressive wave. Principle of superposition of waves, reflection of waves, Standing waves in strings and organ pipes, fundamental mode and harmonics, Beats, Doppler effect in sound UNIT 11: ELECTROSTATICS Electric charges: Conservation of charge, Coulomb’s law-forces between two point charges, forces between multiple charges; superposition principle and continuous charge distribution. Electric field: Electric field due to a point charge, Electric field lines, Electric dipole, Electric field due to a dipole, Torque on a dipole in a uniform electric field. Electric flux, Gauss’s law and its applications to find field due to infinitely long uniformly charged straight wire, uniformly charged infinite plane sheet and uniformly charged thin spherical shell. Electric potential and its calculation for a point charge, electric dipole and system of charges; Equipotential surfaces, Electrical potential energy of a system of two point charges in an electrostatic field. Conductors and insulators, Dielectrics and electric polarization, capacitor, combination of capacitors in series and in parallel, capacitance of a parallel plate capacitor with and without dielectric medium between the plates, Energy stored in a capacitor. UNIT 12: CURRRENT ELECTRICITY Electric current, Drift velocity, Ohm’s law, Electrical resistance, Resistances of different materials, V-I characteristics of Ohmic and nonohmic conductors, Electrical energy and power, Electrical resistivity, Colour code for resistors; Series and parallel combinations of resistors; Temperature dependence of resistance. Electric Cell and its Internal resistance, potential difference and emf of a cell, combination of cells in series and in parallel. Kirchhoff’s laws and their applications. Wheatstone bridge, Metre bridge. Potentiometer - principle and its applications. Biot - Savart law and its application to current carrying circular loop. Ampere’s law and its applications to infinitely long current carrying straight wire and solenoid. Force on a moving charge in uniform magnetic and electric fields. Cyclotron. Force on a current-carrying conductor in a uniform magnetic field. Force between two parallel current-carrying conductors-definition of ampere. Torque experienced by a current loop in uniform magnetic field; Moving coil galvanometer, its current sensitivity and conversion to ammeter and voltmeter. Current loop as a magnetic dipole and its magnetic dipole moment. Bar magnet as an equivalent solenoid, magnetic field lines; Earth’s magnetic field and magnetic elements. Para-, dia- and ferro- magnetic substances. Magnetic susceptibility and permeability, Hysteresis, Electromagnets and permanent magnets. Electromagnetic induction; Faraday’s law, induced emf and current; Lenz’s Law, Eddy currents. Self and mutual inductance. Alternating currents, peak and rms value of alternating current/ voltage; reactance and impedance; LCR series circuit, resonance; Quality factor, power in AC circuits, wattless current. AC generator and transformer. Electromagnetic waves and their characteristics. Transverse nature of electromagnetic waves. Electromagnetic spectrum (radio waves, microwaves, infrared, visible, ultraviolet, Xrays, gamma rays). Applications of e.m. waves. UNIT 16: OPTICS Reflection and refraction of light at plane and spherical surfaces, mirror formula, Total internal reflection and its applications, Deviation and Dispersion of light by a prism, Lens Formula, Magnification, Power of a Lens, Combination of thin lenses in contact, Microscope and Astronomical Telescope (reflecting and refracting) and their magnifyingpowers. Wave optics: wavefront and Huygens’ principle, Laws of reflection and refraction using Huygen’s principle. Interference, Young’s double slit experiment and expression for fringe width. Diffraction due to a single slit, width of central maximum. Resolving power of microscopes and astronomical telescopes, Polarisation, plane polarized light; Brewster’s law, uses of plane polarized light and Polaroids. UNIT 17: DUAL NATURE OF MATTER ANDRADIATION Dual nature of radiation. Photoelectric effect, Hertz and Lenard’s observations; Einstein’s photoelectric equation; particle nature of light. Matter waves-wave nature of particle, de Broglie relation. Davisson-Germer experiment. UNIT 18: ATOMS AND NUCLEI Alpha-particle scattering experiment; Rutherford’s model of atom; Bohr model, energy levels, hydrogen spectrum. Composition and size of nucleus, atomic masses, isotopes, isobars; isotones. Radioactivity-alpha, beta and gamma particles/rays and their properties; radioactive decay law. Mass-energy relation, mass defect; binding energy per nucleon and its variation with mass number, nuclear fission and fusion. UNIT 19: ELECTRONIC DEVICES Semiconductors; semiconductor diode: I-V characteristics in forward and reverse bias; diode as a rectifier; I-V characteristics of LED, photodiode, solar cell and Zener diode; Zener diode as a voltage regulator. Junction transistor, transistor action, characteristics of a transistor; transistor as an amplifier (common emitter configuration) and oscillator. Logic gates (OR, AND, NOT, NAND and NOR). Transistor as a switch. Propagation of electromagnetic waves in the atmosphere; Sky and space wave propagation, Need for modulation, Amplitude and Frequency Modulation, Bandwidth of signals, Bandwidth of Transmission medium, Basic Elements of a Communication System (Block Diagram only). UNIT 21: EXPERIMENTAL SKILLS Familiarity with the basic approach and observations of the experiments and activities: 1. Vernier callipers-its use to measure internal and external diameter and depth of a vessel. 2. Screw gauge-its use to determine thickness/diameter of thin sheet/wire. 3. Simple Pendulum-dissipation of energy by plotting a graph between square of amplitude and time. 4. Metre Scale - mass of a given object by principle of moments. 5. Young’s modulus of elasticity of the material of a metallic wire. 6. Surface tension of water by capillary rise and effect of detergents. 7. Co-efficient of Viscosity of a given viscous liquid by measuring terminal velocity of a given spherical body. 8. Plotting a cooling curve for the relationship between the temperature of a hot body and time. 9. Speed of sound in air at room temperature using a resonance tube. 10. Specific heat capacity of a given (i) solid and (ii) liquid by method of mixtures. 11. Resistivity of the material of a given wire using metre bridge. 12. Resistance of a given wire using Ohm’s law. 13. Potentiometer – (i) Comparison of emf of two primary cells. (ii) Determination of internal resistance of a cell. 14. Resistance and figure of merit of a galvanometer by half deflection method. 15. Focal length of: (i) Convex mirror (ii) Concave mirror, and (iii) Convex lens using parallax method. 16. Plot of angle of deviation vs angle of incidence for a triangular prism. 17. Refractive index of a glass slab using a travelling microscope. 18. Characteristic curves of a p-n junction diode in forward and reverse bias. 19. Characteristic curves of a Zener diode and finding reverse break down voltage. 20. Characteristic curves of a transistor and finding current gain and voltage gain. 21. Identification of Diode, LED, Transistor, IC, Resistor, Capacitor from mixed collection of such items. 22. Using multimeter to: (i) Identify base of a transistor (ii) Distinguish between npn and pnp type transistor (iii) See the unidirectional flow of current in case of a diode and an LED. (iv) Check the correctness or otherwise of a given electronic component (diode, transistor or IC).
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Agreeing with Bill James In 1988, the Bill James Abstract included "A Bill James Primer" , with 15 statements expressing what he deemed to be useful knowledge. On that list was: 2. Talent in baseball is not normally distributed. It is a pyramid. For every player who is 10 percent above the average player, there are probably twenty players who are 10 percent below average. I agree. (Others don't; for further discussion also see here.) But what is this thing called "talent"? Talent is a combination of a high level of skill and sustained, consistent performance. Skill in baseball is measured through metrics such as ERA (earned run average) and OPS (on-base average plus slugging percentage) -- measures that turn counting stats into an efficiency or rate measure. While this type of measure is important, they fail to account for the fact that some players have lengthy careers, while other players have a very short MLB career. Teams will sign long-term contracts with aging superstars because the player's skill is still above average, even though they may have diminished with age. In short, career length becomes a valid proxy for talent. The charts below plot the number of pitchers over the period 1996-2009, by both the number of games played (which favours the relief pitchers) and innings pitched (which favours the starters). During this period a total of 2,134 individuals pitched in MLB -- but the chart shows that very few of them stuck around for any length of time. At the head of the "games" list at 898 is the still-active Mariano Rivera, while the pitcher with the most innings over this period was Greg Maddux (2887.67 innings; and Maddux threw more than 2,100 innings before 1996, as well). These two individuals, and other Hall of Fame calibre pitchers, are out at the far right of the long tail. Close to the origin at the left are pitchers whose entire career lasted but 1/3 of an inning -- a single out. Figure 1: Number of Pitchers, by Career Innings Pitched (1996-2009) Figure 2: Number of Pitchers, by Career Games (1996-2009) But what of the average skill level of those pitchers? Pitchers who get a small amount of MLB experience (fewer than 27 innings) have a higher ERA than those who get more opportunities to pitch. This group -- 27% of all MLB pitchers -- recorded an average ERA of 8.08, compared to 5.15 for the 42% who pitched between 27 to 269 innings, and 4.45 for the 27% who threw between 270 and 1349 innings. The elite, those who pitched 1350 innings and above, recorded the lowest ERA of all, 4.17. In spite of the wide variance in the ERAs of the coffee drinkers, the differences in the mean scores are statistically significant. Figure 3: MLB Pitchers, average ERA, by number of innings pitched (1996-2009) In summary: there is an abundance of players who are less talented than the major league average, while at the same time the number of above-average talents is low. The distribution, at the major league level, is not normal. Just like Bill James said 22 years ago. No comments:
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Golden Ratio Dividers This allows anyone to build a golden ratio divider of any size at all. The method is independent of measurement units (inches, mm, cubits, ad The attached drawing shows the design layout. Note that all angles are either 90 or 45 degrees (It's pretty obvious which are which). Wherever two lines meet, there's a pivot. Decide on the longest measurement you want the dividers to handle. Let's call it L. Either multiply L by 0.618 or divide it by 1.618. The result will be the span between the left point and the "middle" point. Let's call that Dmajor. Then the span between the "middle" point and the right point will be Sminor = L - Smajor. The only other piece of information needed is that the length of a side of a square is (roughly) 0.707 times the length of a diagonal. One of the things that ocurred to me as I made the drawing was that there's no limit to the number of "middle" arms this thing can have, and that even with just one arm, you can set up any ratio you want (eg: divide any span into thirds). Morris Dovey DeSoto Solar DeSoto, Iowa USA
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La Mirada Calculus Tutor Find a La Mirada Calculus Tutor ...It describes how the world around us works, and it is the foundation of the other sciences (chemistry, biology, etc., have their roots in physics). I love talking about and teaching physics, as it can be applied to (and describe) many common real-life situations. For example: the next time you... 11 Subjects: including calculus, physics, statistics, SAT math ...Ultimately, whatever the grade level or current aptitude of the student, I am focused on the specific needs of my students. I take a rigorously individualized approach to tutoring, tailoring my lessons to the precise, personal abilities and objectives of my students. I believe in setting long-t... 58 Subjects: including calculus, English, reading, writing I have taught/tutored for 3 years. I was both a student and graduate assistant at CSULB where I attained a B.S. in Mathematics and a M.S. in Statistics. I have experience tutoring in all mathematics subjects up to and including graduate-level material. 34 Subjects: including calculus, chemistry, English, physics ...My credential is in mathematics (and allows me to teach ANY math course in a high school setting). And my master's is a MS (my degree was through the math department NOT education department at CSULB) in mathematics education where I took half my classes in pure math and half in how to teach math... 13 Subjects: including calculus, geometry, statistics, algebra 2 ...My dream was to be one of the few people to make it to the big leagues. Then I woke up. Still, my knowledge of baseball is immense and I have successfully coached 2 youth teams. 23 Subjects: including calculus, statistics, geometry, accounting
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Cheyney Algebra 2 Tutor Find a Cheyney Algebra 2 Tutor ...Many of Latoya's students appreciate her ability to break down seemingly difficult concepts into simpler more comprehensible ideas through the use of analogies and other tactics. I am a graduate from the University of Pittsburgh with a B.S degree in Pre-Med and a minor in Chemistry which requires knowledge of advanced math. I had a 3.4 GPA. 13 Subjects: including algebra 2, chemistry, geometry, biology ...I have planned and executed numerous lessons for classes of high school students, as well as tutored many independently. I have been trained to teach Trigonometry according to the Common Core Standards. I have planned and executed numerous lessons for classes of high school students, as well as tutored many independently. 11 Subjects: including algebra 2, calculus, geometry, algebra 1 ...I have worked with computers in industry for over twenty years, and led numerous software development projects. My chess experience began when I was a child. In high school, I was the first seat of the chess team. 39 Subjects: including algebra 2, chemistry, trigonometry, statistics ...I previously taught Algebra I, II, III, Geometry, Trigonometry, Precalculus, Calculus, Intro to Statistics, and SAT review in a public school. I have tutored students as well, with tasks ranging from locating weak spots in arithmetic skills, assisting honors students looking for a jump start, he... 12 Subjects: including algebra 2, calculus, geometry, statistics Hi! My name is Helen. I have been teaching for over four years now and have some background in private and public tutoring.I earned my M.S. in Computer Science and B.S. in Statistics and minor in 24 Subjects: including algebra 2, calculus, accounting, Chinese
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Ordnance Survey By Steve Pratchett • How do we measure and describe gradients on maps and in the field? • How does a map indicate gradients? • What is the relationship between gradient and land use? One arrow indicates a gradient of 1 in 7 to 1 in 5 Two arrows indicate a gradient of 1 in 5 or steeper Modelling the locality To develop these ideas, children constructed a 3-D model from the Ordnance Survey map. A section of the map was enlarged in colour (to make it easier to read the contour lines). I then traced over the contour lines with a dark brown pen so that black-and-white copies could be made. The children took the copies and cut around each contour line. They glued their cut-out onto a piece of 5 mm Styrofoam® mounting board (a much cheaper option is to use corrugated cardboard from boxes). The boards gave a convenient arbitrary unit for the interval between each contour line. Although the children were using 5 mm board, the original map had been enlarged by 400%, so distortion was less than x2. The children then cut around the Styrofoam mounted contour lines using keyhole saws. When the children viewed the model from the side they, in effect, experienced a cross section of the landscape. The children deduced that the number of arrows indicated the steepness of the hill. A field trip with map and model The ideal situation is to take the children on the field trip to a steep hill. When I did this the benefits were clear. On the outward journey, one group of children navigated with the map and the other with the model. They were delighted to find the model echoing even the slightest change in the incline of the road. Their fingers became the car, kinaesthetically tracing the route and mimicking its movement as it ascended and descended. This exercise also helped with map orientation skills, as the model had to be turned to face the way we were going. Where a field trip is impractical, good discussion results can be obtained by using photographs. Relating gradient to land use The children were encouraged to deduce why areas of mixed woodland appeared in particular locations on their Ordnance Survey map of the Bere Peninsula. These tended to occur along the sides of stream and river valleys. The rest of the peninsula is covered by farmland belonging to numerous dairy and arable farms, such as Hole & Well Farm. 3D Model The children offered several explanations – 'The trees grow near the rivers because they get more water.' 'The trees are planted to stop the valleys eroding.' 'The contour lines are close together so it's steep ...you can't farm the fields, it's too steep here.' The latter response from one observant child stimulated a flurry of discussion as the children began to check all the patches of woodland on the map and model to see if they only occurred where the contour lines were closely packed. This proved to be the case. To reinforce this observation, the children were given a tiny toy tractor and tried driving it on different parts of the three-dimensional model of the peninsula. On the steeply wooded slopes, the tractor rolled over into the river or stream! This led to a discussion of why farmers did not plough steeply sloping land for arable or cereal production and the identification of more such areas on the local map. Some humorous comments were also made about the problems dairy cows would have 'rolling down the hill!' Try the following suggestions on modelling gradients as ratios and gradients as percentages. Lots of lovely links with numeracy! *Styrofoam is a registered trade mark of the Dow Chemical company Modelling gradients as percentages using metre rulers and elastic To develop children's skills in measuring and expressing gradients as percentages, metre rulers were used. A metre ruler laid flat on the ground gives a convenient horizontal distance of 100 units (cms) and another ruler held upright at one end gives a selection of the same units for vertical climb. A length of shirring elastic can be used to link the two rulers for example, a triangle formed in this way with a 100 cm base and 20 cm height has a 20% gradient. This means that a toy car would climb 20 cms vertically for every 100 cms it travels horizontally. 20 units out of every 100 = 20%. Using the same triangle, it is also possible to translate percentages into ratios and vice versa. If the child travels 5 cms along the horizontal ruler with a toy car and then measures up vertically from this point to the elastic slope, the height will be 1 cm. This is a 1: 5 triangle. These ratios can be multiplied e.g.: 8 cms along .......................... 1.6 cms up 12 cms along .......................... 2.4 cms up 16 cms along .......................... 3.2 cms up 100 cms along .......................... 20 cms up (20%) Extension of work on gradients - understanding the shape of the ground An extension to work on gradients and their corresponding contour line patterns is to model convex and concave slopes in clay. The children slice the models into horizontal layers at regular intervals and then draw around each slice to create 'contour lines'. The models can be directly compared to the configuration of contour lines they generate, highlighting the relationship between the change in gradients and the change in spacing between the contours. This work will lay a foundation for using contours to understand the shape of the ground when map-reading. With thanks to Kim Wilde, Headteacher, at Bere Alston Primary School.
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Probabilty problem October 21st 2010, 06:14 PM #1 Oct 2010 Probabilty problem Hello forum :] I am in need of some help on this probability problem. The probability of being born on a Friday the 13th is 1/214. Assume the days of people's birth are independent of each other. (a) You meet two new friends; what is the probability that both new friends were born on a Friday the 13th? I got this one, just use the multiplication rule so: (1/214)(1/214) = 1/45796 (b) You meet 31 new friends; what is the probability that at least one of these new friends was born on a Friday the 13th? I cant figure this out. If they were disjoint then I could just use the addition rule, but they aren't so I am very confused. Any help will be greatly appreciated. Hello, Phodot! The probability of being born on a Friday the 13th is 1/214. Assume the days of people's birth are independent of each other. (a) You meet two new friends. What is the probability that both new friends were born on a Friday the 13th? I got this one, just use the multiplication rule so: $(\frac{1}{214})(\frac{1}{214}) \:=\: \frac{1}{45,\!796}$ . Right! (b) You meet 31 new friends; what is the probability that at least one of these new friends was born on a Friday the 13th? The opposite of "at least one" is "none." The probability that none were borh on Friday the 13th is: . $(\frac{213}{214})^{31}$ Therefore: . $P(\text{at least one Friday the 13th}) \;=\;1 - \left(\frac{213}{214}\right)^{31} \;\approx\;13.5\%$ Thank you very much :] October 21st 2010, 08:42 PM #2 Super Member May 2006 Lexington, MA (USA) October 21st 2010, 09:04 PM #3 Oct 2010
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13th July 2012: Scott Aaronson (MIT) Title: Quantum Computing and the Limits of the Efficiently Computable By Scott Aaronson (Associate Professor of Electrical Engineering and Computer Science at MIT) Abstract: I'll discuss what can and can't be feasibly computed according to physical law. I'll argue that this is a fundamental question, not only for mathematics and computer science, but also for physics; and that the infeasibility of certain computational problems (such as NP-complete problems) could plausibly be taken as a physical principle, analogous to the Second Law or the impossibility of superluminal signalling. I'll first explain the basics of computational complexity, including the infamous P versus NP problem and the Extended Church-Turing Thesis. Then I'll discuss quantum computers: what they are, whether they can be scalably built, and what's known today about their capabilities and limitations. Lastly, I'll touch on speculative models of computation that would go even beyond quantum computers, using (for example) closed timelike curves or nonlinearities in the Schrodinger equation. I'll emphasize that, even if "intractable" computations occur in a particular description of a physical system, what really matters is whether those computations have observable consequences. Bio: Scott Aaronson is an Associate Professor of Electrical Engineering and Computer Science at Massachusetts Institute of Technology (MIT). He received his PhD in computer science from University of California, Berkeley and did postdocs at the Institute for Advanced Study and the University of Waterloo. Scott's research interests center around fundamental limits on what can efficiently be computed in the physical world. This has entailed studying quantum computing, the most powerful model of computation we have based on known physical theory. He also writes a popular blog (www.scottaaronson.com/blog), and is the creator of the Complexity Zoo (www.complexityzoo.com), an online encyclopedia of computational complexity theory. He is the recipient of NSF's Alan T. Waterman Award for 2012. This article was published on Nov 7, 2012
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The Black Vault Message Forums at1with0 wrote:Infinity might be a misnomer. We keep arguing over the same concepts every couple of years. http://en.wikipedia.org/wiki/Infinity#A ... e_sciences From the perspective of cognitive scientists George Lakoff, concepts of infinity in mathematics and the sciences are metaphors, based on what they term the Basic Metaphor of Infinity (BMI), namely the ever-increasing sequence <1,2,3,...>. Infinity is a metaphor and can be manipulated in various ways mathematically. Indefinite succession? "I can conceive of nothing in religion, science, or philosophy, that is anything more than the proper thing to wear, for a while." ~ Charles Fort The only reason there is a set of natural numbers, i.e. the only reason there is an infinite set, is that it is assumed (the axiom of infinity). AFAIK there is no way to prove that there is a set N such that x is in N iff x is a natural number. "it is easy to grow crazy" the definitional parameters of the set concept are not well formed. What is truth? Baby, don't hurt me, don't hurt me... no more. "I can conceive of nothing in religion, science, or philosophy, that is anything more than the proper thing to wear, for a while." ~ Charles Fort Truth is the state of the status quo encapsulating both the objective and the subjective eye of the beholder. "I can conceive of nothing in religion, science, or philosophy, that is anything more than the proper thing to wear, for a while." ~ Charles Fort Individual self stands in contrast to the continuum of all possible selves. Hopefully At1with0 will be able to figure out how to get his rich self from the Richie Rich universe to cross the impassible gulf between universes into this universe, in order to give him his desperately sought after prize. khanster wrote:Individual self stands in contrast to the continuum of all possible selves. Hopefully At1with0 will be able to figure out how to get his rich self from the Richie Rich universe to cross the impassible gulf between universes into this universe, in order to give him his desperately sought after prize. The pot of gold argument just shows that not every conceivable event occurs somewhere in the multiverse. "it is easy to grow crazy" at1with0 wrote: khanster wrote:Individual self stands in contrast to the continuum of all possible selves. Hopefully At1with0 will be able to figure out how to get his rich self from the Richie Rich universe to cross the impassible gulf between universes into this universe, in order to give him his desperately sought after prize. The pot of gold argument just shows that not every conceivable event occurs somewhere in the multiverse. Actually you mentioned the pot of gold argument just off the top of your head in an insincere fashion. You never really seriously meditated on the pot of gold nor did you ever work on your powers of concentration, so why should you stand out amongst the infinite number of other at1with0's? What makes you so special and deserving of that pot of gold?
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Got Homework? Connect with other students for help. It's a free community. • across MIT Grad Student Online now • laura* Helped 1,000 students Online now • Hero College Math Guru Online now Here's the question you clicked on: using sin, cos or tan find the value of X • 8 months ago • 8 months ago Your question is ready. Sign up for free to start getting answers. is replying to Can someone tell me what button the professor is hitting... • Teamwork 19 Teammate • Problem Solving 19 Hero • Engagement 19 Mad Hatter • You have blocked this person. • ✔ You're a fan Checking fan status... Thanks for being so helpful in mathematics. If you are getting quality help, make sure you spread the word about OpenStudy. This is the testimonial you wrote. You haven't written a testimonial for Owlfred.
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On multidimensional curves with Hilbert property - NIC Series , 2002 "... this paper a parallelisable and cheap method based on space-filling curves is proposed. The partitioning is embedded into the parallel solution algorithm using multilevel iterative solvers and adaptive grid refinement. Numerical experiments on two massively parallel computers prove the efficienc ..." Cited by 8 (0 self) Add to MetaCart this paper a parallelisable and cheap method based on space-filling curves is proposed. The partitioning is embedded into the parallel solution algorithm using multilevel iterative solvers and adaptive grid refinement. Numerical experiments on two massively parallel computers prove the efficiency of this approach , 2007 "... Abstract. Let X = S G where G is a countable group and S is a finite set. A cellular automaton (CA) is an endomorphism T: X → X (continuous, commuting with the action of G). Shereshevsky [14] proved that for G = Z d with d> 1 no CA can be forward expansive, raising the following conjecture: For G = ..." Cited by 3 (1 self) Add to MetaCart Abstract. Let X = S G where G is a countable group and S is a finite set. A cellular automaton (CA) is an endomorphism T: X → X (continuous, commuting with the action of G). Shereshevsky [14] proved that for G = Z d with d> 1 no CA can be forward expansive, raising the following conjecture: For G = Z d, d> 1 the topological entropy of any CA is either zero or infinite. Morris and Ward [11], proved this for linear CA’s, leaving the original conjecture open. We show that this conjecture is false, proving that for any d there exist a d-dimensional CA with finite, nonzero topological entropy. We also discuss a measure-theoretic counterpart of this question for measure-preserving CA’s. 1. "... Two-dimensional R-trees are a class of spatial index structures in which objects are arranged to enable fast window queries: report all objects that intersect a given query window. One of the most successful methods of arranging the objects in the index structure is based on sorting the objects acco ..." Cited by 3 (2 self) Add to MetaCart Two-dimensional R-trees are a class of spatial index structures in which objects are arranged to enable fast window queries: report all objects that intersect a given query window. One of the most successful methods of arranging the objects in the index structure is based on sorting the objects according to the positions of their centres along a two-dimensional Hilbert spacefilling curve. Alternatively one may use the coordinates of the objects ’ bounding boxes to represent each object by a four-dimensional point, and sort these points along a four-dimensional Hilbert-type curve. In experiments by Kamel and Faloutsos and by Arge et al. the first solution consistently outperformed the latter when applied to point data, while the latter solution clearly outperformed the first on certain artificial rectangle data. These authors did not specify which four-dimensional Hilbert-type curve was used; many exist. In this paper we show that the results of the previous papers can be explained by the choice of the fourdimensional Hilbert-type curve that was used and by the way it was rotated in four-dimensional space. By selecting a curve that has certain properties and choosing the right rotation one can combine the strengths of the two-dimensional and the four-dimensional approach into one, while avoiding their apparent weaknesses. The effectiveness of our approach is demonstrated with experiments on various data sets. For real data taken from VLSI design, our new curve yields R-trees with query times that are better than those of R-trees that were obtained with previously used curves. 1 - in: ESA "... Space-filling curves can be used to organise points in the plane into bounding-box hierarchies (such as R-trees). We develop measures of the bounding-box quality of space-filling curves that express how effective different space-filling curves are for this purpose. We give general lower bounds on th ..." Cited by 3 (2 self) Add to MetaCart Space-filling curves can be used to organise points in the plane into bounding-box hierarchies (such as R-trees). We develop measures of the bounding-box quality of space-filling curves that express how effective different space-filling curves are for this purpose. We give general lower bounds on the bounding-box quality measures and on locality according to Gotsman and Lindenbaum for a large class of space-filling curves. We describe a generic algorithm to approximate these and similar quality measures for any given curve. Using our algorithm we find good approximations of the locality and the bounding-box quality of several known and new space-filling curves. Surprisingly, some curves with relatively bad locality by Gotsman and Lindenbaum’s measure, have good bounding-box quality, while the curve with the best-known locality has relatively bad bounding-box quality. 1 "... A discrete space-filling curve provides a linear traversal/indexing of a multi-dimensional grid space. This paper presents an application of random walk to the study of inter-clustering of space-filling curves and an analytical study on the inter-clustering performances of 2-dimensional Hilbert and ..." Cited by 1 (1 self) Add to MetaCart A discrete space-filling curve provides a linear traversal/indexing of a multi-dimensional grid space. This paper presents an application of random walk to the study of inter-clustering of space-filling curves and an analytical study on the inter-clustering performances of 2-dimensional Hilbert and z-order curve families. Two underlying measures are employed: the mean inter-cluster distance over all inter-cluster gaps and the mean total inter-cluster distance over all subgrids. We show how approximating the mean inter-cluster distance statistics of continuous multi-dimensional space-filling curves fits into the formalism of random walk, and derive the exact formulas for the two statistics for both curve families. The excellent agreement in the approximate and true mean inter-cluster distance statistics suggests that the random walk may furnish an effective model to develop approximations to clustering and locality statistics for space-filling curves. Based upon the analytical results, the asymptotic comparisons indicate that z-order curve family performs better than Hilbert curve family with respect to both statistics. "... The geometric structural complexity of spatial objects does not render an intuitive distance metric on the data space that measures spatial proximity. However, such a metric provides a formal basis for analytical work in transformation-based multidimensional spatial access methods, including localit ..." Add to MetaCart The geometric structural complexity of spatial objects does not render an intuitive distance metric on the data space that measures spatial proximity. However, such a metric provides a formal basis for analytical work in transformation-based multidimensional spatial access methods, including locality preservation of the underlying transformation and distance-based spatial queries. We study the Hausdorff distance metric on the space of multidimensional polytopes, and prove a tight relationship between the metric on the original space of k-dimensional hyperrectangles and the standard p-normed metric on the transform space of 2kdimensional points under the corner transformation, which justifies the effectiveness of the transformationbased technique in preserving spatial locality. Keywords: databases, multidimensional spatial access methods, corner transformation, locality , 2007 "... Abstract. Let X = S G where G is a countable group and S is a finite set. A cellular automaton (CA) is an endomorphism T: X → X (continuous, commuting with the action of G). Shereshevsky [13] proved that for G = Z d with d> 1 no CA can be forward expansive, raising the following conjecture: For G = ..." Add to MetaCart Abstract. Let X = S G where G is a countable group and S is a finite set. A cellular automaton (CA) is an endomorphism T: X → X (continuous, commuting with the action of G). Shereshevsky [13] proved that for G = Z d with d> 1 no CA can be forward expansive, raising the following conjecture: For G = Z d, d> 1 the topological entropy of any CA is either zero or infinite. Morris and Ward [10], proved this for linear CA’s, leaving the original conjecture open. We show that this conjecture is false, proving that for any d there exist a d-dimensional CA with finite, nonzero topological entropy. We also discuss a measure-theoretic counterpart of this question for measure-preserving CA’s. 1. , 909 "... Column-oriented indexes—such as projection or bitmap indexes—are compressed by run-length encoding to reduce storage and increase speed. Sorting the tables improves compression. On realistic data sets, permuting the columns in the right order before sorting can reduce the number of runs by a factor ..." Add to MetaCart Column-oriented indexes—such as projection or bitmap indexes—are compressed by run-length encoding to reduce storage and increase speed. Sorting the tables improves compression. On realistic data sets, permuting the columns in the right order before sorting can reduce the number of runs by a factor of two or more. For many cases, we prove that the number of runs in table columns is minimized if we sort columns by increasing cardinality. Yet—maybe surprisingly—we must sometimes maximize the number of runs to minimize the index size. Experimentally, sorting based on Hilbert space-filling curves is poor at minimizing the number of runs. Key words: "... Two-dimensional R-trees are a class of spatial index structures in which objects are arranged to enable fast window queries: report all objects that intersect a given query window. One of the most successful methods of arranging the objects in the index structure is based on sorting the objects acco ..." Add to MetaCart Two-dimensional R-trees are a class of spatial index structures in which objects are arranged to enable fast window queries: report all objects that intersect a given query window. One of the most successful methods of arranging the objects in the index structure is based on sorting the objects according to the positions of their centres along a two-dimensional Hilbert space-filling curve. Alternatively one may use the coordinates of the objects ’ bounding boxes to represent each object by a four-dimensional point, and sort these points along a four-dimensional Hilbert-type curve. In experiments by Kamel and Faloutsos and by Arge et al. the first solution consistently outperformed the latter when applied to point data, while the latter solution clearly outperformed the first on certain artificial rectangle data. These authors did not specify which four-dimensional Hilbert-type curve was used; many exist. In this paper we show that the results of the previous papers can be explained by the choice of the four-dimensional Hilbert-type curve that was used and by the way it was rotated in fourdimensional space. By selecting a curve that has certain properties and choosing the right rotation one can combine the strengths of the two-dimensional and the four-dimensional approach into one, while avoiding their apparent weaknesses. The effectiveness of our approach is demonstrated with
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The u/v coordinates for the hemisphere x ≥ 0 are derived from the phi and theta angles, as follows: u = sin(θ) cos(φ) v = sin(θ) sin(φ) In these expressions, φ and θ are the phi and theta angles, respectively. In terms of azimuth and elevation, the u and v coordinates are u = cos(el) sin(az) v = sin(el) The values of u and v satisfy the inequalities –1 ≤ u ≤ 1 –1 ≤ v ≤ 1 u^2 + v^2 ≤ 1 Conversely, the phi and theta angles can be written in terms of u and v tan(φ) = v/u sin(θ) = sqrt(u^2 + v^2) The azimuth and elevation angles can also be written in terms of u and v sin(el) = v tan(az) = u/sqrt(1 – u^2 – v^2) The φ angle is the angle from the positive y-axis toward the positive z-axis, to the vector's orthogonal projection onto the yz plane. The φ angle is between 0 and 360 degrees. The θ angle is the angle from the x-axis toward the yz plane, to the vector itself. The θ angle is between 0 and 180 degrees. The figure illustrates φ and θ for a vector that appears as a green solid line. The coordinate system is relative to the center of a uniform linear array, whose elements appear as blue circles. The coordinate transformations between φ/θ and az/el are described by the following equations
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R-statistics blog Category Archives: R bloggers (Written by Ian Fellows) The RForge build error has been fixed. the package can now be tried with: install.packages("Deducer",,"http://www.rforge.net",type="source") As prolific as the CRAN website is of packages, there are several packages to R that succeeds in standing out for their wide spread use (and quality), Hadley Wickhams ggplot2 and plyr are two such And today (through twitter) Hadley has updates the rest of us with the news: just released new versions of plyr and ggplot2. source versions available on cran, compiled will follow soon #rstats Going to the CRAN website shows that plyr has gone through the most major update, with the last update (before the current one) taking place on 2009-06-23. And now, over a year later, we are presented with plyr version 1, which includes New functions, New features some Bug fixes and a much anticipated Speed improvements. ggplot2, has made a tiny leap from version 0.8.7 to 0.8.8, and was previously last updated on 2010-03-03. Me, and I am sure many R users are very thankful for the amazing work that Hadley Wickham is doing (both on his code, and with helping other useRs on the help lists). So Hadley, thank you! Here is the complete change-log list for both packages: Continue reading Update (07.07.10): The function in this post has a more mature version in the “arm” package. See at the end of this post for more details. * * * * Imagine you want to give a presentation or report of your latest findings running some sort of regression analysis. How would you do it? This was exactly the question Wincent Rong-gui HUANG has recently asked on the R mailing list. One person, Bernd Weiss, responded by linking to the chapter “Plotting Regression Coefficients” on an interesting online book (I have never heard of before) called “Using Graphs Instead of Tables” (I should add this link to the free statistics e-books list…) Letter in the conversation, Achim Zeileis, has surprised us (well, me) saying the following I’ve thought about adding a plot() method for the coeftest() function in the “lmtest” package. Essentially, it relies on a coef() and a vcov() method being available – and that a central limit theorem holds. For releasing it as a general function in the package the code is still too raw, but maybe it’s useful for someone on the list. Hence, I’ve included it below. (I allowed myself to add some bolds in the text) So for the convenience of all of us, I uploaded Achim’s code in a file for easy access. Here is an example of how to use it: data("Mroz", package = "car") fm <- glm(lfp ~ ., data = Mroz, family = binomial) coefplot(fm, parm = -1) I hope Achim will get around to improve the function so he might think it worthy of joining his“lmtest” package. I am glad he shared his code for the rest of us to have something to work with in the * * * Update (07.07.10): Thanks to a comment by David Atkins, I found out there is a more mature version of this function (called coefplot) inside the {arm} package. This version offers many features, one of which is the ability to easily stack several confidence intervals one on top of the other. It works for baysglm, glm, lm, polr objects and a default method is available which takes pre-computed coefficients and associated standard errors from any suitable model. (Notice that the Poisson model in comparison with the binomial models does not make much sense, but is enough to illustrate the use of the function) data("Mroz", package = "car") M1<- glm(lfp ~ ., data = Mroz, family = binomial) M2<- bayesglm(lfp ~ ., data = Mroz, family = binomial) M3<- glm(lfp ~ ., data = Mroz, family = binomial(probit)) coefplot(M2, xlim=c(-2, 6), intercept=TRUE) coefplot(M1, add=TRUE, col.pts="red", intercept=TRUE) coefplot(M3, add=TRUE, col.pts="blue", intercept=TRUE, offset=0.2) (hat tip goes to Allan Engelhardt for help improving the code, and for Achim Zeileis in extending and improving the narration for the example) Resulting plot * * * Lastly, another method worth mentioning is the Nomogram, implemented by Frank Harrell’a rms package. About prize baring contests Competition with prizes are an amazing thing. If you are not sure of that, I urge you to listened to Peter Diamandis talk about his experience with the X prize (start listening at minute 11:40): At short – prizes can give up to 1 to 50 ratio of return on investment of the people giving funding to the prize. The money is spent only when results are achieved. And there is a lot of value in terms of public opinion and publicity. And the best of all (for the promoter of the competition) – prizes encourage people to take risks (at their own expense) in order to get results done. All of that said, I look at prize baring competition as something worth spreading, especially in cases where the results of the winning team will be shared with the public. About the IEEE ICDM Contest The IEEE ICDM Contest (“Road Traffic Prediction for Intelligent GPS Navigation”), seems to be one of those cases. Due to a polite request, I am republishing here the details of this new competition, in the hope that some of my R colleagues will bring the community some pride Continue reading (Written by Ian Fellows) Below is a link to the first of a weekly (or bi-weekly) screen-cast vlog of my progress building a GUI for the ggplot2 package. comments and suggestions are more than welcome, and can e-mailed to me at: hefell@gmail.com About Clustergrams In 2002, Matthias Schonlau published in “The Stata Journal” an article named “The Clustergram: A graph for visualizing hierarchical and . As explained in the abstract: In hierarchical cluster analysis dendrogram graphs are used to visualize how clusters are formed. I propose an alternative graph named “clustergram” to examine how cluster members are assigned to clusters as the number of clusters increases. This graph is useful in exploratory analysis for non-hierarchical clustering algorithms like k-means and for hierarchical cluster algorithms when the number of observations is large enough to make dendrograms impractical. A similar article was later written and was (maybe) published in “computational statistics”. Both articles gives some nice background to known methods like k-means and methods for hierarchical clustering, and then goes on to present examples of using these methods (with the Clustergarm) to analyse some datasets. Personally, I understand the clustergram to be a type of parallel coordinates plot where each observation is given a vector. The vector contains the observation’s location according to how many clusters the dataset was split into. The scale of the vector is the scale of the first principal component of the data. Clustergram in R (a basic function) After finding out about this method of visualization, I was hunted by the curiosity to play with it a bit. Therefore, and since I didn’t find any implementation of the graph in R, I went about writing the code to implement it. The code only works for kmeans, but it shows how such a plot can be produced, and could be later modified so to offer methods that will connect with different clustering algorithms. How does the function work: The function I present here gets a data.frame/matrix with a row for each observation, and the variable dimensions present in the columns. The function assumes the data is scaled. The function then goes about calculating the cluster centers for our data, for varying number of clusters. For each cluster iteration, the cluster centers are multiplied by the first loading of the principal components of the original data. Thus offering a weighted mean of the each cluster center dimensions that might give a decent representation of that cluster (this method has the known limitations of using the first component of a PCA for dimensionality reduction, but I won’t go into that in this post). Finally all of our data points are ordered according to their respective cluster first component, and plotted against the number of clusters (thus creating the clustergram). My thank goes to Hadley Wickham for offering some good tips on how to prepare the graph. Here is the code (example follows) The R function can be downloaded from here Corrections and remarks can be added in the comments bellow, or on the github code page. Example on the iris dataset The iris data set is a favorite example of many R bloggers when writing about R accessors , Data Exporting, Data importing, and for different visualization techniques. So it seemed only natural to experiment on it here. source("http://www.r-statistics.com/wp-content/uploads/2012/01/source_https.r.txt") # Making sure we can source code from github par(cex.lab = 1.5, cex.main = 1.2) Data <- scale(iris[,-5]) # notice I am scaling the vectors) clustergram(Data, k.range = 2:8, line.width = 0.004) # notice how I am using line.width. Play with it on your problem, according to the scale of Y. Here is the output: Looking at the image we can notice a few interesting things. We notice that one of the clusters formed (the lower one) stays as is no matter how many clusters we are allowing (except for one observation that goes way and then beck). We can also see that the second split is a solid one (in the sense that it splits the first cluster into two clusters which are not “close” to each other, and that about half the observations goes to each of the new clusters). And then notice how moving to 5 clusters makes almost no difference. Lastly, notice how when going for 8 clusters, we are practically left with 4 clusters (remember – this is according the mean of cluster centers by the loading of the first component of the PCA on the If I where to take something from this graph, I would say I have a strong tendency to use 3-4 clusters on this data. But wait, did our clustering algorithm do a stable job? Let’s try running the algorithm 6 more times (each run will have a different starting point for the clusters) source("http://www.r-statistics.com/wp-content/uploads/2012/01/source_https.r.txt") # Making sure we can source code from github Data <- scale(iris[,-5]) # notice I am scaling the vectors) par(cex.lab = 1.2, cex.main = .7) par(mfrow = c(3,2)) for(i in 1:6) clustergram(Data, k.range = 2:8 , line.width = .004, add.center.points = T) Resulting with: (press the image to enlarge it) Repeating the analysis offers even more insights. First, it would appear that until 3 clusters, the algorithm gives rather stable results. From 4 onwards we get various outcomes at each iteration. At some of the cases, we got 3 clusters when we asked for 4 or even 5 clusters. Reviewing the new plots, I would prefer to go with the 3 clusters option. Noting how the two “upper” clusters might have similar properties while the lower cluster is quite distinct from the other By the way, the Iris data set is composed of three types of flowers. I imagine the kmeans had done a decent job in distinguishing the three. Limitation of the method (and a possible way to overcome it?!) It is worth noting that the current way the algorithm is built has a fundamental limitation: The plot is good for detecting a situation where there are several clusters but each of them is clearly “bigger” then the one before it (on the first principal component of the data). For example, let’s create a dataset with 3 clusters, each one is taken from a normal distribution with a higher mean: source("http://www.r-statistics.com/wp-content/uploads/2012/01/source_https.r.txt") # Making sure we can source code from github Data <- rbind( cbind(rnorm(100,0, sd = 0.3),rnorm(100,0, sd = 0.3),rnorm(100,0, sd = 0.3)), cbind(rnorm(100,1, sd = 0.3),rnorm(100,1, sd = 0.3),rnorm(100,1, sd = 0.3)), cbind(rnorm(100,2, sd = 0.3),rnorm(100,2, sd = 0.3),rnorm(100,2, sd = 0.3)) clustergram(Data, k.range = 2:5 , line.width = .004, add.center.points = T) The resulting plot for this is the following: The image shows a clear distinction between three ranks of clusters. There is no doubt (for me) from looking at this image, that three clusters would be the correct number of clusters. But what if the clusters where different but didn’t have an ordering to them? For example, look at the following 4 dimensional data: source("http://www.r-statistics.com/wp-content/uploads/2012/01/source_https.r.txt") # Making sure we can source code from github Data <- rbind( cbind(rnorm(100,1, sd = 0.3),rnorm(100,0, sd = 0.3),rnorm(100,0, sd = 0.3),rnorm(100,0, sd = 0.3)), cbind(rnorm(100,0, sd = 0.3),rnorm(100,1, sd = 0.3),rnorm(100,0, sd = 0.3),rnorm(100,0, sd = 0.3)), cbind(rnorm(100,0, sd = 0.3),rnorm(100,1, sd = 0.3),rnorm(100,1, sd = 0.3),rnorm(100,0, sd = 0.3)), cbind(rnorm(100,0, sd = 0.3),rnorm(100,0, sd = 0.3),rnorm(100,0, sd = 0.3),rnorm(100,1, sd = 0.3)) clustergram(Data, k.range = 2:8 , line.width = .004, add.center.points = T) In this situation, it is not clear from the location of the clusters on the Y axis that we are dealing with 4 clusters. But what is interesting, is that through the growing number of clusters, we can notice that there are 4 “strands” of data points moving more or less together (until we reached 4 clusters, at which point the clusters started breaking up). Another hope for handling this might be using the color of the lines in some way, but I haven’t yet figured out how. Clustergram with ggplot2 Hadley Wickham has kindly played with recreating the clustergram using the ggplot2 engine. You can see the result here: And this is what he wrote about it in the comments: I’ve broken it down into three components: * run the clustering algorithm and get predictions (many_kmeans and all_hclust) * produce the data for the clustergram (clustergram) * plot it (plot.clustergram) I don’t think I have the logic behind the y-position adjustment quite right though. Conclusions (some rules of thumb and questions for the future) In a first look, it would appear that the clustergram can be of use. I can imagine using this graph to quickly run various clustering algorithms and then compare them to each other and review their stability (In the way I just demonstrated in the example above). The three rules of thumb I have noticed by now are: 1. Look at the location of the cluster points on the Y axis. See when they remain stable, when they start flying around, and what happens to them in higher number of clusters (do they re-group 2. Observe the strands of the datapoints. Even if the clusters centers are not ordered, the lines for each item might (needs more research and thinking) tend to move together – hinting at the real number of clusters 3. Run the plot multiple times to observe the stability of the cluster formation (and location) Yet there is more work to be done and questions to seek answers to: • The code needs to be extended to offer methods to various clustering algorithms. • How can the colors of the lines be used better? • How can this be done using other graphical engines (ggplot2/lattice?) – (Update: look at Hadley’s reply in the comments) • What to do in case the first principal component doesn’t capture enough of the data? (maybe plot this graph to all the relevant components. but then – how do you make conclusions of it?) • What other uses/conclusions can be made based on this graph? I am looking forward to reading your input/ideas in the comments (or in reply posts). useR!2010 is coming. I am going to give two talks there (I will write more of that soon), but in the meantime, please note that the online registration deadline is coming to an end. This was published on the R-help mailing list today: The final registration deadline for the R User Conference is June 20, 2010, one week away. Later registration will not be possible on site! Conference webpage: http://www.R-project.org/useR-2010 Conference program: http://www.R-project.org/useR-2010/program.html The conference is scheduled for July 21-23, 2010, and will take place at the campus of the National Institute of Standards and Technology (NIST) in Gaithersburg, Maryland, USA.
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Geometry proof October 4th 2008, 06:49 AM #1 Junior Member Aug 2008 Geometry proof A radius drawn to bisect a chord in a circle will always meet the chord at 90 degrees. Use a mathematical method (that does not use vectors), to prove this. I've never been too great with geometric proofs let the chord be segment AB. let the circle center be point O. let M be the intersection point of the bisecting radius and chord AB. M is the midpoint of AB ... why? now, prove that triangle OMA is congruent to triangle OMB, then use corresponding parts of congruent triangles to show that angle OMA is congruent to angle OMB. from this point, it should be easy to show that OM is perpendicular to AB. formally, you can't just say M is the midpoint of AB ... the reason must be given, i.e. "definition of a segment bisector". you do understand that every statement in a proof requires a reason, correct? that's all I'm trying to tell you. October 4th 2008, 07:14 AM #2 October 4th 2008, 07:22 AM #3 Junior Member Aug 2008 October 4th 2008, 07:37 AM #4 October 4th 2008, 07:39 AM #5 Junior Member Aug 2008 October 4th 2008, 08:10 AM #6 October 4th 2008, 08:12 AM #7 Junior Member Aug 2008
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Fibonacci problem, proof by induction? November 13th 2012, 09:27 PM #1 Nov 2012 alpha = (1+ sqrt5)/2 and beta = (1-sqrt5)/2 alpha^2 = 1 + alpha and beta^2 = 1+ beta Use induction to prove that for all integers n >= 1 we have alpha^n = f(n-1)+ f(n)*(alpha) and beta^n = f(n-1)+ f(n)*(beta) I've did my base case and plug in k+1 to n but I can't get them equal to each other. Please help, I've been playing with these numbers for hours. Re: Fibonacci problem, proof by induction? Having demonstrated the base case $P_1$ is true, then state the induction hypothesis $P_k$ Multiply through by $\alpha$: Now, since $F_{n+1}=F_{n}+F_{n-1}$, can you continue? Re: Fibonacci problem, proof by induction? so alpha^(k+1) = (alpha)*f(k+1) + f(k) sorry, I still don't know how is this a proof alpha^n = f(n-1)+ f(n)*(alpha) Re: Fibonacci problem, proof by induction? We may write this result as: You see, we have arrived at $P_{k+1}$ which we derived from $P_k$, completing the proof by induction. Observe that this is the same as the induction hypothesis, except $k$ is replaced with $k+1$. This means it is true for all $n\in\mathbb{N}$. Have you learned the analogy of climbing a ladder or falling dominoes to mathematical induction? Re: Fibonacci problem, proof by induction? oh okay, thanks. This problem is just very different to the kind of Fibonacci problem I've been doing. But they're just the same in the end. Thanks again : ) Re: Fibonacci problem, proof by induction? Glad to help, and welcome to the forum! November 13th 2012, 09:46 PM #2 November 13th 2012, 10:01 PM #3 Nov 2012 November 13th 2012, 10:19 PM #4 November 13th 2012, 10:34 PM #5 Nov 2012 November 13th 2012, 10:38 PM #6
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Solution for a particular column vector implies solution for all column vectors. February 1st 2011, 07:31 PM Solution for a particular column vector implies solution for all column vectors. Let $A$ be a square matrix. Show that if the system $AX=B$ has a unique solution for some particular column vector $B$, then it has a unique solution for all $B$. So I'm not really sure how to go about this since there's no assumption that $A$ is invertible, and I'm assuming I have to utilize row operations or the like, but I just can't make any connections. Any help would be appreciated, thanks. February 1st 2011, 08:56 PM Let $A$ be a square matrix. Show that if the system $AX=B$ has a unique solution for some particular column vector $B$, then it has a unique solution for all $B$. So I'm not really sure how to go about this since there's no assumption that $A$ is invertible, and I'm assuming I have to utilize row operations or the like, but I just can't make any connections. Any help would be appreciated, thanks. Here is my thoughts on the question. Every solution to a linear system can be decomposed into two separate pieces. $X=X_c+X_p$ where $X_c$ is the complimentary solution (the solution to the homogeneous equation) and $X_p$ is a particular solution. Since we know the solution is unique for some particular $b$ We have $Ax=A(x_c+x_p)=b$ Since the solution is unique The complementary solution cannot have any free parameters. e.g the kernel of this Matrix has only one vector in it and since $\vec{0} \in x_c$ the only solution to the system $Av=0$ is $v=0$ This will give the desired conclusion. February 1st 2011, 09:09 PM I'm not sure I exactly follow (we haven't covered kernel, etc). Are you saying that since the solution is unique, it must be the case that $x_{c}$ is the zero column vector? And I'm not sure I make the connection to how it follows that there must be a unique solution for any $B$. February 2nd 2011, 12:34 AM If $AX=B_0$ has unique solution, then $E_n\cdot\ldots\cdot E_1AX=E_n\cdot\ldots\cdot E_1B_0\Leftrightarrow UX=E_n\cdot\ldots\cdot E_1B_0$ (where $U$ is a row echelon form) has unique solution. This implies that all leading coefficients of $U$ are different from $0$. Now, you can conclude. Fernando Revilla February 2nd 2011, 04:16 PM Whew, I get it now. Thanks so much!
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14. How Strongly Do Physical Characteristics Of ... | Chegg.com 14. How strongly do physical characteristics of sisters and brothers correlate? Here are data on the heights (in inches) of 11 adult pairs. Brother height (x) 71 68 66 67 70 71 70 73 72 65 66 Sister height (y) 69 64 65 63 65 62 65 64 66 59 62 Use your calculator to answer a, b and c below and answer all questions in 3 decimal places. Show your work for d ~ g for full credit. a. The correlation between brother and sister heights b. The mean of the brother and sister height c. The standard deviation of brother and sister height d. The slope of the least-square regression line, use the answers found from a and c. e. The intercept of the least-squares regression line, use the answers found from b and d. f. The equation of the least-square regression line g. The residual corresponding to the example data point (67” for a brother height and 63” for his sister) Statistics and Probability
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La Mirada Calculus Tutor Find a La Mirada Calculus Tutor ...It describes how the world around us works, and it is the foundation of the other sciences (chemistry, biology, etc., have their roots in physics). I love talking about and teaching physics, as it can be applied to (and describe) many common real-life situations. For example: the next time you... 11 Subjects: including calculus, physics, statistics, SAT math ...Ultimately, whatever the grade level or current aptitude of the student, I am focused on the specific needs of my students. I take a rigorously individualized approach to tutoring, tailoring my lessons to the precise, personal abilities and objectives of my students. I believe in setting long-t... 58 Subjects: including calculus, English, reading, writing I have taught/tutored for 3 years. I was both a student and graduate assistant at CSULB where I attained a B.S. in Mathematics and a M.S. in Statistics. I have experience tutoring in all mathematics subjects up to and including graduate-level material. 34 Subjects: including calculus, chemistry, English, physics ...My credential is in mathematics (and allows me to teach ANY math course in a high school setting). And my master's is a MS (my degree was through the math department NOT education department at CSULB) in mathematics education where I took half my classes in pure math and half in how to teach math... 13 Subjects: including calculus, geometry, statistics, algebra 2 ...My dream was to be one of the few people to make it to the big leagues. Then I woke up. Still, my knowledge of baseball is immense and I have successfully coached 2 youth teams. 23 Subjects: including calculus, statistics, geometry, accounting
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THE NATURAL COMMUNITIES OF VIRGINIA CLASSIFICATION OF ECOLOGICAL COMMUNITY GROUPS Second Approximation (Version 2.6) Information current as of July, 2013 Ordination is a multivariate technique that arranges vegetation samples in relation to each other based on compositional similarity and relative species-abundances. Ordination procedures summarize multidimensional data in a reduced coordinate system, extracting those axes that explain the most variation in the data. DCR-DNH ecologists use non-metric multidimensional scaling (NMDS) , an ordination technique based on indirect gradient analysis that maximizes, to the extent possible, the rank-order (i.e ., non-parametric) correlation between inter-sample dissimilarity and inter-sample distance in ordination space. The results of ordination analyses are depicted by diagrams, in which each point represents a plot and the distance between points roughly indicates the degree of compositional similarity. Statistically significant correlations between measured environmental variables and sample coordinates on each axis may be plotted as vectors and overlain on the diagram. The direction of a vector indicates the direction of maximum correlation through ordination space, while vector line lengths are determined by the strength of the correlation. This diagram shows a two-dimensional ordination of the same dataset used to illustrate cluster analysis. Symbols indicate the four groups identified in the dendrogram and significant environmental gradients are plotted.
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Finding largest no Join Date Nov 2007 Rep Power I have following code for finding largest no among 3 nos. Java Code: import java.util.*; public class LargestNo{ public static void main (String [] arg) { Scanner scan = new Scanner (System.in); int [] numbers = new int [3]; int x; int largestNumber; System.out.print("Put in (three) numbers"); for (x=0; x<numbers.length; x++) { numbers[x]=scan.nextInt (); largestNumber = 0; for (x=0; x<numbers.length; x++) { if (x == 0) { largestNumber = numbers[0]; if (numbers[x] > largestNumber) { largestNumber = numbers[x]; System.out.println("The largest number is " + largestNumber); I want to print the largest no and also its position in the array. how to do that? Please give me tips. Join Date Aug 2007 Rep Power You can have a separate int variable for position. something like this... Java Code: import java.util.*; public class LargestNo{ public static void main (String [] arg) { Scanner scan = new Scanner (System.in); int [] numbers = new int [3]; int x; int largestNumber; int pos=0;//position in the array System.out.print("Put in (three) numbers"); for (x=0; x<numbers.length; x++) { numbers[x]=scan.nextInt (); largestNumber = 0; for (x=0; x<numbers.length; x++) { if (x == 0) { largestNumber = numbers[0]; pos = 0; if (numbers[x] > largestNumber) { largestNumber = numbers[x]; pos = x;//x is the position of the number in the array. System.out.println("The largest number is " + largestNumber); System.out.println("Position of the largest number:"+pos); Join Date Nov 2007 Rep Power Ok kool. Cant I fetch the index from array just specifying the value. For example, I am assuming that array will only contain unique values and having a value I now want to get its index from Just like same thing you have to done. Use another dummy variable. At each of the comparison you have done to check whether the number is large or small, update that dummy value. Say first number is large, your dummy should be 0. In the next iteration the second number is small, still your dummy should be 0, because it holds the position. I think my logic is clear. At the same time, I think you have use additional } at last. Compile and check it. Join Date Nov 2007 Rep Power Thanks Eranga. But consider the following: For example, I am assuming that array will only contain unique values and having a value I now want to get its index from array. I'm not get you. What you mean unique values. Between array index and array values there is no connection. Can you explain little more. Join Date Nov 2007 Rep Power No there is no connection. I think you know that, array is indexing by starting with 0. That mean maximum indexing is less than one by number of element. element 12 5 23 index 0 1 2 #of element 1 2 3 Join Date Aug 2007 Rep Power There is actually a way to get the index..Arrays has a method binarySearch(array to be searched,key) which returns the position of the specified key.. Using it in your program: Java Code: import java.util.*; public class LargestNo{ public static void main (String [] arg) { Scanner scan = new Scanner (System.in); int [] numbers = new int [3]; int x; int largestNumber; //int pos=0;//position in the array int index=0; System.out.print("Put in (three) numbers"); for (x=0; x<numbers.length; x++) { numbers[x]=scan.nextInt (); largestNumber = 0; for (x=0; x<numbers.length; x++) { if (x == 0) { largestNumber = numbers[0]; //pos = 0; if (numbers[x] > largestNumber) { largestNumber = numbers[x]; //pos = x;//x is the position of the number in the array. index = Arrays.binarySearch(numbers, largestNumber); System.out.println("The largest number is " + largestNumber); System.out.println("Position of the largest number:"+index); I am not sure though if this would be a correct way to get the index of an array element... Yep that's correct. One of the efficient way it is. The way what I've told is the basis way to do it, comparing how to find the largest number. Because the same way should follow. Join Date Nov 2007 Rep Power Its clear now. Thanks all of you.
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KS3 Maths Revision Ronald Wayne was the third founder of the business "Apple"! However he sold his 10% stake for how much money in 1976? Mouseover to see answer $800 - Apple is now valued roughly at $620 Billion! KS3 Maths Revision (Resources for school year 7, year 8 and year 9) Whether you love Maths or you hate it, you can be encouraged by the fact that 50% of all doctors graduate in the bottom half of their class! If you love Maths then we hope our KS3 Maths quizzes help you love it a little more and if you hate Maths then we hope the quizzes help you hate it a little less. Whatever else happens, you will agree that interactive Maths revision quizzes are more exciting than Maths text books! Maths is a subject that needs to be learned step by step and because of this we categorize our quizzes using the same levels, ages and years as the National Curriculum. If you are confused by all the numbers then we hope the table below helps you to revise the right subjects at the right time: Level = 3/4: Age = 11/12: Year = 7 Level = 5/6: Age = 12/13: Year = 8 Level = 7/8: Age = 13/14: Year = 9 How To Play Each quiz consists of 10 questions and each question has 4 multiple choice answers. At the top of each quiz you are given a choice of how you want to play it and this affects what happens when you provide an incorrect answer. You can either have the correct answer given immediately, or you can choose to have the questions presented again at the end of the quiz. To print any of the quizzes (both questions and answers) click the “Print” link at the bottom of the quiz
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Perth Amboy Math Tutor Find a Perth Amboy Math Tutor ...I have taken Calculus 1, Calculus 2, Multivariable calculus, Differential Equations and Discrete Mathematics. My computer science coursework has focused on object oriented programming (Java) and databases (SQL). I have taken various history classes as well and one of my hobbies is teaching mysel... 11 Subjects: including algebra 1, algebra 2, American history, calculus ...I am senior student majoring in electrical engineering in December 2011. I am currently a campus tutor at a local college on the subject of Math (from Algebra to calculus), General physics 1&2, electrical engineering and computer engineering courses. I have been tutoring at the college of Staten island for 4 years. 23 Subjects: including algebra 2, electrical engineering, ASVAB, differential equations ...Algebra II/Trigonometry:I cover as much topics as the student needs or all the topics, especially the ratio of those most pertinent to the Regents exam. From Algebraic expressions, Functions and Relations, Composition and Inverses of Functions, Exponential and Logarithmic Functions, Trigonometri... 47 Subjects: including statistics, SAT math, accounting, writing Hello! My name is Vishal J., and I'm just finishing my graduate studies in urban planning and policy development, focusing on regional economic analysis and international development. During my studies, I have been a teaching assistant for public health, public policy, and epidemiology undergraduate courses. 45 Subjects: including econometrics, statistics, reading, English ...I am a certified Math teacher grade (5-9), with over 3 years of successful teaching experience. I am confident in my ability and passion to become helpful for your child. I have earned a Bachelor’s Degree in Mathematics as well gained Certification in Mathematics grade (5-9). Attending M.S. in ED (Brooklyn College), Middle Childhood (5-9)- Mathematics. 4 Subjects: including trigonometry, algebra 1, prealgebra, precalculus
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Material Results Search Materials Return to What's new in MERLOT Get more information on the MERLOT Editors' Choice Award in a new window. Get more information on the MERLOT Classics Award in a new window. Get more information on the JOLT Award in a new window. Go to Search Page View material results for all categories Click here to go to your profile Click to expand login or register menu Select to go to your workspace Click here to go to your Dashboard Report Click here to go to your Content Builder Click here to log out Search Terms Enter username Enter password Please give at least one keyword of at least three characters for the search to work with. The more keywords you give, the better the search will work for you. select OK to launch help window cancel help You are now going to MERLOT Help. It will open a new window. A collection of tutorials (Flash and Java) on various applications of integration including area between two curves, volumes,... see more Material Type: Lawrence Husch Date Added: Jul 19, 2006 Date Modified: Oct 22, 2013 A Calculus Tutorial developed at Oregon State University. "Contains wonderful illustrations ofcalculus concepts using stories... see more Material Type: William Bogley and Robby Robson Date Added: Aug 08, 2000 Date Modified: Feb 08, 2011 This subsite of Mathematics Tutorials and Problems (with applets) is divided into Interactive Tutorials, Calculus Problems,... see more Material Type: kader dendane Date Added: Jun 28, 2008 Date Modified: Oct 22, 2013 This site contains an electronic version of a Calculus textbook linked to a collection of interactive Java applets. The book... see more Material Type: Dan Sloughter Date Added: Nov 14, 2005 Date Modified: Oct 22, 2013 Tutorials and animations (Flash and Java) on finding volumes of solids of revolution; helpful for students who are visual... see more Material Type: Lawrence Husch Date Added: Jul 20, 2006 Date Modified: Jan 28, 2013 The CCP includes modules that combine the flexibility and connectivity of the Web with the power of computer algebra systems... see more Material Type: David Smith & Lawrence Moore, CCP Co-Directors Date Added: Sep 25, 2005 Date Modified: Jul 23, 2007 Quoted from the site: [This site contains...] "Free mathematics tutorials to help you explore and gain deep understanding of... see more Material Type: kader dendane Date Added: Jun 20, 2008 Date Modified: Jan 24, 2013 This webpage has all lecture material, homeworks, homework solutions, and computer laboratories for a Calculus for Biology... see more Material Type: Joe Mahaffy Date Added: Apr 27, 2001 Date Modified: Mar 05, 2011 Collection of tutorials for the first year calculus student. Includes collections of online quizzes and drill problems. see more Material Type: Lawrence Husch Date Added: Apr 28, 2000 Date Modified: Oct 22, 2013 The CCP includes modules that combine the flexibility and connectivity of the Web with the power of computer algebra systems... see more Material Type: David Smith & Lawrence Moore, CCP Co-Directors Date Added: Jan 26, 2006 Date Modified: Oct 07, 2010 Results page 1 of 3 2 3 Next
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real derivative of the magnitude of a complex function? October 13th 2010, 05:29 PM #1 Oct 2010 real derivative of the magnitude of a complex function? Dear all, I'm new to these forums and not sure if this is in the right section, but calculus I think is the main part of the problem. So I'm trying to solve an optimization problem that requires me to take the (real) derivative of the magnitude of a complex function. Given a real vector $\mathbf{x} \in \mathbb{R}^n$ and a function $f : \mathbb{R}^n \rightarrow \mathbb{C}$, how do I compute $abla |f(\mathbf{x})| = ?$ I know that the complex derivative of the magnitude of a complex function is undefined, but the real derivative should be defined, right? For those interested in the entire problem, the function is of the form $f(\mathbf{x}) = \mathbf{c}^T \mathbf{M(x) y(x)}$, where $\mathbf{M}$ is a complex matrix and $\mathbf{y}$ is a complex vector, but both are functions of a set of real inputs $\mathbf{x}$. $\ mathbf{c}$ is a constant vector. I'm fairly confident I can take the derivative of $f(\mathbf{x})$, but it's the magnitude that's giving me trouble. Appreciate any help or insight. Thanks so much! g(x)=|f(x)| is only an ordinary function from R^n to R. So grad(g) = ( g_1, g_2, ..., g_n), where g_i is the i-th partial derivative. For your case, f is actually a map from R^n to R^2, g=\sqrt<f,f>. Then you can do the differential via chain rule and the Leibniz rule that D<f1,f2> = <Df1, f2> + <f1, Df2>. <,> is the inner product of R^2. Thanks for the prompt reply. My interpretation of your post is that I need to somehow write the complex function f(x) into f1(x) = Re(f) and f2(x) = Im(f) when I can then go ahead and use the chain rule on sqrt(f1^2 + f2^2). Unfortunately this requires me to write down f1 and f2 explicitly which is probably possible to do but likely to be messy. For example, Re (M * y) = Re(M) Re(y) - Im(M) Im(y), but M and y themselves are expressed in block matrix form are written in terms of multiple products of smaller complex matrices, so I'm afraid calculating Re and Im will quickly go out of hand. Is there an alternative that can directly allow me to use the chain rule on the magnitude function, provided I can calculate grad(f)? Thanks again! |z|^2 = z z* where z* is the complex conjugate. So d|z|/dt = 1/(2|z|) (dz/dt z* + z dz*/dt) = 1/(2|z|) (dz/dt z* + z (dz/dt)* ) = Re(dz/dt z*)/|z| not sure this will reduce some of the effort or not hmm... you know, it might, actually. I'm going to go try it and see if it's easier. Thanks for your help! If, using the standard notation, z= x+ iy, f(z)= u(x,y)+ iv(x,y), then $|f(z)|= \sqrt{u^2(x,y)+ v^2(x,y)$ and $abla |f(z)|= \frac{\partial \sqrt{u^2+ v^2}}{\partial x}\vec{i}+ \frac{\partial \ sqrt{u^2+ v^2}}{\partial y}\vec{j}$. More generally, if f is a function from $R^n$ to C, then $f(x)= u(x_1, x_2, ..., x_n)+ iv(x_1, x_2, ...,, x_n)$, $|f(x)|= \sqrt{u^2+ v^2}$ and $abla |f(x)|= \sum_{i= 1}^n \frac{\partial\sqrt{u^2+ v^2}}{\partial x_i}\vec{e_i}$ where $e_i$ is the unit vector in the $x_i$ direction. October 13th 2010, 06:12 PM #2 Senior Member Mar 2010 Beijing, China October 13th 2010, 06:23 PM #3 Oct 2010 October 13th 2010, 08:54 PM #4 Senior Member Mar 2010 Beijing, China October 13th 2010, 09:15 PM #5 Oct 2010 October 14th 2010, 04:30 AM #6 MHF Contributor Apr 2005
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Weights for etale cohomology: why does Deligne's definition work? up vote 3 down vote favorite For a field $K$ and a variety $X/K$ (whose characteristic could be $0$) I need a 'simple' explanation for the (Deligne's) method of defining weights of the $l$-adic etale cohomology of $\overline{X}$ (the base change of $X$ to the algebraic closure of $K$). Which 'complicated' statements does one need to define and study weights, and what statements here could be proved 'easily' (using basic properties of etale cohomology)? What is the best reference for obtaining an 'understanding' of these things (I prefer reading in English and in Russian:))? Upd. I know some references on the subject (Weil II, Kiehl-Weissauer? SGA IV3, SGAVII2); yet it is difficult to understand which parts of these books contain the information I need. Does there exist any 'guide' to any of these texts? On the other hand, "Weights in arithmetic geometry" by Jannsen is too short. etale-cohomology reference-request ag.algebraic-geometry 1 There might be some useful things in the text "Cohomology of algebraic varieties" by Danilov, or rather the parts of it about étale cohomology. It appeared in English translation in an EMS volume, the Russion original can be found here: mi.mathnet.ru/eng/intf124 – Dan Petersen Oct 21 '12 at 11:32 Thank you; this is an interesting text! – Mikhail Bondarko Oct 22 '12 at 5:47 add comment 2 Answers active oldest votes Complicated (the special case $f: X \to \mathbf{F}_q$ proper smooth is Weil I!): Let $\mathcal{F}$ be mixed of weight $\leq i$. Then $R^q\pi_!\mathcal{F}$ is mixed of weight $\leq q+i$ up vote 1 (see Deligne, Weil II, Théorème 1 (3.3.1) or Kiehl-Weissauer, Theorem I.7.1, strengthened in I.9.3) down vote 1 Thank you! Yet I also need to bound weights from below.:) Certainly, I can apply the Verdier duality to this end; yet is there an 'easier' way? – Mikhail Bondarko Oct 20 '12 at 19:59 add comment It seems that your question is not well defined unless $K$ is finitely generated over its prime field. See for instance Jannsen, Uwe Weights in arithmetic geometry. Jpn. J. Math. 5 (2010), no. 1, 73–102. http://arxiv.org/abs/1003.0927 or http://www.springerlink.com/content/207j13t274004070/ up vote 1 down vote and also (this is in French) Deligne, Pierre Poids dans la cohomologie des variétés algébriques. Proceedings of the International Congress of Mathematicians (Vancouver, B. C., 1974), Vol. 1, pp. 79–85 Canad. Math. Congress, Montreal, Que., 1975. http://www.mathunion.org/ICM/ICM1974.1/Main/icm1974.1.0079.0086.ocr.pdf About the first reference: do you know where I can find some details on the isomorphism $b_{\eta,s}$ in the formula (2.3)? – Mikhail Bondarko Oct 20 '12 at 21:03 You can find all details there Théorie des topos et cohomologie étale des schémas. Tome 3.Séminaire de Géométrie Algébrique du Bois-Marie 1963–1964 (SGA 4). Lecture Notes in Mathematics, Vol. 305. springerlink.com/content/n880177446r8 – Niels Oct 21 '12 at 7:52 I'm sorry; could you give a more precise reference? I know the smooth and proper base change theorems; yet how do they help here? – Mikhail Bondarko Oct 21 '12 at 9:29 add comment Not the answer you're looking for? Browse other questions tagged etale-cohomology reference-request ag.algebraic-geometry or ask your own question.
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Math - Please Help Posted by Barb on Sunday, February 17, 2013 at 10:25pm. A right circular cone has a volume of 140 in^3. The height of the cone is the same length as the diameter of the base. Find the radius and height. • Math - Please Help - Jeff, Sunday, February 17, 2013 at 11:37pm We know the formula for the Volume of a Right Circular Cone is given by V=140 in^3 The height of the cone = diameter of the base. The diameter = 2 times the radius, so h = 2r The formula for Volume can now be written as which simplifies to You plug in 140 in^3 for V and solve for r. Then you can plug the value you find for r into the equation h=2r • Math - Please Help - Reiny, Monday, February 18, 2013 at 12:13am V = (1/3 π r^2 h , but h = 2r 3V = π r^2 (2r) = 2π r^3 420 = 2πr^3 r^3 = 210/π r = (210/π)^(1/3) = 4.0584 r = 4.0584 h = 8.11683 V = (1/3)π(4.0584)^2 (8.11683) = 139.9989.. , not bad Related Questions Math - A right circular cylinder with a height of 20 cm and a right circular ... math - A right circular cone is inscribed inside a sphere. The right circular ... Calculus - Show that a right-circular cylinder of greatest volume that can be ... math - Consider the right circular cone shown. if the radius of the circular ... math - Consider the right circular cone shown. If the radius of the circular ... math - Consider the right circular cone shown. If the radius of the circular ... Calculus - A right circular cone is inscribed in a sphere of radius r. Find the... Calculus - A right circular cone is inscribed in a sphere of radius r. Find the ... Geometry - One right circular cone is set inside a larger circular cone. The ... Math 214 - How do you find the volume of a right circular cone with a hemisphere...
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Find a Scarsdale Calculus Tutor ...I have an MS and a PhD in mathematics from Yale University, and summa cum laude BS and MS in mathematics from the former USSR. A graduate of one of the Soviet Union's elite math-and-physics high schools, I was also a multiple Mathematics Olympiad winner. What I can do for you: (1) SAT/ACT and ISEE/SSAT test prep. 27 Subjects: including calculus, physics, statistics, geometry ...I have been tutoring math and physics for six years, and would be happy to provide references for past or current students on demand. I take an interactive approach to tutoring, and encourage students to give lots of feedback, dictate the pace, and maintain a constant dialogue with me. I don't ... 10 Subjects: including calculus, physics, geometry, statistics ...My professional background has been centered around finance and information technology. Recently, I have been at home raising two children. From a teaching and tutoring standpoint, I am always patient and encouraging. 12 Subjects: including calculus, geometry, statistics, finance ...I have both Bachelor and Master in chemical engineering from City College of New York (CCNY) and MBA with project management concentration from DeVry University. The chemical engineering degree provided strong graduate foundation in math, chemistry and physics, while my MBA provided me with grad... 21 Subjects: including calculus, chemistry, statistics, geometry Hi parents and students, My name is Natalie and I am a forthcoming high school mathematics teacher. I graduated from a NYC specialized high school and I am currently studying at New York University, majoring in Mathematics Secondary Education. I have been a volunteer math tutor for the last 5 years, and have grown to work quickly and effectively on any mathematics subject. 19 Subjects: including calculus, geometry, biology, algebra 1
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Got Homework? Connect with other students for help. It's a free community. • across MIT Grad Student Online now • laura* Helped 1,000 students Online now • Hero College Math Guru Online now Here's the question you clicked on: is there an easier way than listing all possibilities then solving to find all rational roots for P(x)=0 • one year ago • one year ago Best Response You've already chosen the best response. we list all of the possibles to satisfy the p/q theorem actually it is called the possible rational theorem but it is not necessary to list them all when solving for all zeros of a polynomial if nothing else, it gives us a starting point of what value a zero could be Your question is ready. Sign up for free to start getting answers. is replying to Can someone tell me what button the professor is hitting... • Teamwork 19 Teammate • Problem Solving 19 Hero • Engagement 19 Mad Hatter • You have blocked this person. • ✔ You're a fan Checking fan status... Thanks for being so helpful in mathematics. If you are getting quality help, make sure you spread the word about OpenStudy. This is the testimonial you wrote. You haven't written a testimonial for Owlfred.
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the first resource for mathematics New stability and stabilization for switched neutral control systems. (English) Zbl 1198.93187 Summary: This paper concerns stability and stabilization issues for switched neutral systems and presents new classes of piecewise Lyapunov functionals and multiple Lyapunov functionals, based on which, two new switching rules are introduced to stabilize the neutral systems. One switching rule is designed from the solution of the so-called Lyapunov-Metzler linear matrix inequalities. The other is based on the determination of average dwell time computed from a new class of linear matrix inequalities (LMIs). And then, state-feedback control is derived for the switched neutral control system mainly based on the state switching rules. Finally, three examples are given to demonstrate the effectiveness of the proposed method. Editorial remark: There are doubts about a proper peer-reviewing procedure of this journal. The editor-in-chief has retired, but, according to a statement of the publisher, articles accepted under his guidance are published without additional control. 93D15 Stabilization of systems by feedback 34K20 Stability theory of functional-differential equations 34K40 Neutral functional-differential equations 93C23 Systems governed by functional-differential equations 93C30 Control systems governed by other functional relations
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[Numpy-discussion] Best way to construct/slice 3-dimensional ndarray from multiple 2d ndarrays? Aronne Merrelli aronne.merrelli@gmail.... Wed Aug 17 12:46:12 CDT 2011 On Wed, Aug 17, 2011 at 9:04 AM, Keith Hughitt <keith.hughitt@gmail.com>wrote: > Also, when subclassing ndarray and calling obj = data.view(cls) for an > ndarray "data", does this copy the data into the new object by value or > reference? The method which extracts the 2d slice actually returns a > subclass of ndarray created using the extracted data, so this is why I ask. I think it should pass a reference - the following code suggests the subclass is sharing the same fundamental array object. You can use the .base attribute of the ndarray object to see if it is a view back to another ndarray object: import numpy as np class TestClass(np.ndarray): def __new__(cls, inp_array): return inp_array.view(cls) In [2]: x = np.ones(5) In [3]: obj = TestClass(x) In [4]: id(x), id(obj), id(obj.base) Out[4]: (23517648, 19708080, 23517648) In [5]: print x, obj [ 1. 1. 1. 1. 1.] [ 1. 1. 1. 1. 1.] In [6]: x[2] = 2 In [7]: print x, obj [ 1. 1. 2. 1. 1.] [ 1. 1. 2. 1. 1.] If you change the TestClass.__new__() to: "return np.array(inp_array).view(cls)" then you will make a copy of the input array instead, if that is needed. In that case, it looks like the .base attribute is a new ndarray, copied from the input array. [PS - also note that .base is set to None, if the ndarray is not a view into another ndarray; it turns out that None has a valid object number, which confused me at first - see id(None).] -------------- next part -------------- An HTML attachment was scrubbed... URL: http://mail.scipy.org/pipermail/numpy-discussion/attachments/20110817/4f4825ad/attachment.html More information about the NumPy-Discussion mailing list
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10.1.1 Applications and Extensions Next: 10.1.2 The Components of Up: DIME: Portable Software Previous: DIME: Portable Software The most efficient speed for aircraft flight is just below the speed of sound: the transonic regime. Simulations of flight at these speeds consume large quantities of computer time, and are a natural candidate for a DIME application. In addition to the complex geometries of airfoils and turbines for which these simulations are required, the flow tends to develop singular regions or shocks in places that cannot be predicted in advance; the adaptive refinement capability of a DIME mesh allows the mesh to be fine and detail resolved near shocks while keeping the regions of smooth flow coarsely meshed for economy (Section 12.3). The version of DIME developed within C10.1.7. The manifold may, however, be embedded in a higher-dimensional space. In collaboration with the Biology division at Caltech, we have simulated the electrosensory system of the weakly electric fish Apteronotus leptorhynchus. The simulation involves creating a mesh covering the skin of the fish, and using the boundary element method to calculate field strengths in the three-dimensional space surrounding the fish (Section 12.2). In the same vein of embedding the mesh in higher dimensions, we have simulated a bosonic string of high-energy physics, embedding the mesh in up to 26 spatial dimensions. The problem here is to integrate over not only all positions of the mesh nodes, but also over all triangulations of the mesh (Section 7.2). The information available to a DIME application is certain data stored in the elements and nodes of the mesh. When doing finite-element calculations, one would like a somewhat higher level of abstraction, which is to refer to functions defined on a domain, with certain smoothness constraints and boundary conditions. We have made a further software layer on top of DIME to facilitate this: DIMEFEM. With this we may add, multiply, differentiate and integrate functions defined in terms of the Lagrangian finite-element family, and define linear, bilinear, and nonlinear operators acting on these functions. When a bilinear operator is defined, a variational principle may be solved by conjugate-gradient methods. The preconditioner for the CG method may in itself involve solving a variational principle. The DIMEFEM package has been applied to a sophisticated incompressible flow algorithm (Section 10.2). Next: 10.1.2 The Components of Up: DIME: Portable Software Previous: DIME: Portable Software Guy Robinson Wed Mar 1 10:19:35 EST 1995
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When is there a deRham duality relation between the fundamental class and a top form.? up vote 1 down vote favorite Hi, everyone: I am reading a small expository paper on properties of CP^2, in which the intersection form is defined as an integral of the wedge of two forms $w_1$, $w_2$, and these forms $w_1$, $w_2$ (no problem with compact support, since CP^2 is compact) seem to have been obtained from the fundamental class [z] of H[2](CP^2)-- a copy of CP^1 (embedded in CP^2), after which we integrate $w:=w1\wedge w2$ to get the intersection number. I am curious on whether I am reading the above correctly, i.e., that the volume form in CP^2 is obtained by using the fund. class [z] in H[2]. If not, would someone explain; if this is correct, if we are we using some form of deRham's theorem to turn a purely topological object like [z] into an object like $w$, for which we must have a differentiable structure defined)? Thanks in Advance. homology cohomology dg.differential-geometry I took the liberty of editing the formatting of your question a little - hope that's OK, if not let me know. – Yemon Choi Apr 28 '10 at 23:46 Short answer - for all compact oriented manifolds. – Somnath Basu Apr 29 '10 at 1:36 add comment 1 Answer active oldest votes Consider a suitably small tubular neighbourhood $\mathcal{N}$ of $\mathbb{CP}^1$, thought of as sitting inside $\mathbb{CP}^2$. Then $\mathcal{N}$ locally looks like $\mathbb{CP}^1\times D_2$. The volume form $\omega$ of $\mathbb{CP}^1$ is not necessarily a $2$-form in $\mathbb{CP}^2$. However, one can imagine changing it so that we have new $2$-form $\widetilde{\omega}$ in $ \mathbb{CP}^2$, supported in $\mathcal{N}$, such that $\widetilde{\omega}$ restrcited to $\{p\}\times D_2$ (for $p\in\mathbb{CP}^1$) looks like a smooth bump function which integrates to $1$. up vote This can be taken to be $w_1$ in your case. Now assume you take your copy of $\mathbb{CP}^1$ inside $\mathbb{CP}^2$ and perturb it a bit (i.e., make it transversal to itself) to get another 1 down copy. Apply what we said before and get $w_2$ supported in a suitable tubular neighbourhood of this perturbed copy. Now integrating $w_1\wedge w_2$ over $\mathbb{CP}^2$ gives you an vote integration over balls around points where self-intersections occur. The normalization were so chosen that it counts the intersection number of $\mathbb{CP}^1$ with itself. add comment Not the answer you're looking for? Browse other questions tagged homology cohomology dg.differential-geometry or ask your own question.
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Navy Electricity and Electronics Training Series (NEETS) Module 12—Modulation Principles i - ix 1-1 to 1-10 1-11 to 1-20 1-21 to 1-30 1-31 to 1-40 1-41 to 1-50 1-51 to 1-60 1-61 to 1-70 1-71 to 1-75 2-1 to 2-10 2-11 to 2-20 2-21 to 2-30 2-31 to 2-40 2-41 to 2-50 2-51 to 2-60 2-61 to 2-64 3-1 to 3-10 3-11 to 3-20 3-21 to 3-30 3-31 to 3-35 AI-1 to AI-6, Index-1 to 2, Assignment 1 , 2 is referred to as the MODULATED WAVE and is the waveform that is transmitted through space. When the modulated wave is received and demodulated, the original component waves (carrier and modulating waves) are reproduced with their respective frequencies, phases, and amplitudes unchanged. Modulation of a carrier can be achieved by any of several methods. Generally, the methods are named for the sine-wave characteristic that is altered by the modulation process. In this module, you will study AMPLITUDE MODULATION, which includes CONTINUOUS-WAVE MODULATION. You will also learn about two forms of ANGLE MODULATION (FREQUENCY MODULATION and PHASE MODULATION). A special type of modulation, known as PULSE MODULATION, will also be discussed. Before we present the methods involved in developing modulation, you need to study a process that is essential to the modulation of a carrier, known as heterodyning. To help you understand the operation of heterodyning circuits, we will begin with a discussion of LINEAR and NONLINEAR devices. In linear devices, the output rises and falls directly with the input. In nonlinear devices, the output does not rise and fall directly with the input. Whether the impedance of a device is linear or nonlinear can be determined by comparing the change in current through the device to the change in voltage applied to the device. The simple circuit shown in view (A) of figure 1-4 is used to explain this process. Figure 1-4A.—Circuit with one linear impedance. First, the current through the device must be measured as the voltage is varied. Then the current and voltage values can be plotted on a graph, such as the one shown in view (B), to determine the impedance of the device. For example, assume the voltage is varied from 0 to 200 volts in 50-volt steps, as shown in view (B). At the first 50-volt point, the ammeter reads 0.5 ampere. These ordinates are plotted as point a in view (B). With 100 volts applied, the ammeter reads 1 ampere; this value is plotted as point b. As these steps are continued, the values are plotted as points c and d. These points are connected with a straight line to show the linear relationship between current and voltage. For every change in voltage applied to the device, a proportional change occurs in the current through the device. When the change in current is proportional to the change in applied voltage, the impedance of the device is linear and a straight line is developed in the graph. Figure 1-4B.—Circuit with one linear impedance. The principle of linear impedance can be extended by connecting two impedance devices in series, as shown in figure 1-5, view (A). The characteristics of both individual impedances are determined as explained in the preceding section. For example, assume voltmeter V1 shows 50 volts and the ammeter shows 0.5 ampere. Point a in view (B) represents this ordinate. In the same manner, increasing the voltage in increments of 50 volts gives points b, c, and d. Lines Z1 and Z2 show the characteristics of the two impedances. The total voltage of the series combination can be determined by adding the voltages across Z1 and Z2. For example, at 0.5 ampere, point a (50 volts) plus point e (75 volts) produces point i (125 volts). Also, at 1 ampere, point b plus point f produces point j. Line Z1 + Z2 represents the combined voltage-current characteristics of the two devices. Figure 1-5A.—Circuit with two linear impedances. Figure 1-5B.—Circuit with two linear impedances. View (A) of figure 1-6 shows two impedances in parallel. View (B) plots the impedances both individually (Z1 and Z2) and combined (Z1 x Z2)/(Z1 + Z2). Note that Z1 and Z2 are not equal. At 100 volts, Z1 has 1 ampere of current plotted at point b and Z2 has 0.5 ampere plotted at point f. The coordinates of the equivalent impedance of the parallel combination are found by adding the current through Z1 to the current through Z2. For example, at 100 volts, point b is added to point f to determine point j (1.5 amperes). Figure 1-6.—Circuit with parallel linear impedances. Positive or negative voltage values can be used to plot the voltage-current graph. Figure 1-7 shows an example of this situation. First, the voltage versus current is plotted with the battery polarity as shown in view (A). Then the battery polarity is reversed and the remaining voltage versus current points are plotted. As a result, the line shown in view (C) is obtained. Figure 1-7A.—Linear impedance circuit. Figure 1-7B.—Linear impedance circuit. Figure 1-7C.—Linear impedance circuit The battery in view (A) could be replaced with an ac generator, as shown in view (B), to plot the characteristic chart. The same linear voltage-current chart would result. Current flow in either direction is directly proportional to the change in voltage. In conclusion, when dc or sine-wave voltages are applied to a linear impedance, the current through the impedance will vary directly with a change in the voltage. The device could be a resistor, an air-core inductor, a capacitor, or any other linear device. In other words, if a sine-wave generator output is applied to a combination of linear impedances, the resultant current will be a sine wave which is directly proportional to the change in voltage of the generator. The linear impedances do not alter the waveform of the sine wave. The amplitude of the voltage developed across each linear component may vary, or the phase of the wave may shift, but the shape of the wave will remain the same. You have studied that a linear impedance is one in which the resulting current is directly proportional to a change in the applied voltage. A nonlinear impedance is one in which the resulting current is not directly proportional to the change in the applied voltage. View (A) of figure 1-8 illustrates a circuit which contains a nonlinear impedance (Z), and view (B) shows its voltage-current curve. Figure 1-8A.—Nonlinear impedance circuit. Figure 1-8B.—Nonlinear impedance circuit. As the applied voltage is varied, ammeter readings which correspond with the various voltages can be recorded. For example, assume that 50 volts yields 0.4 milliampere (point a), 100 volts produces 1 milliampere (point b), and 150 volts causes 2.2 milliamperes (point c). Current through the nonlinear impedance does not vary proportionally with the voltage; the chart is not a straight line. Therefore, Z is a nonlinear impedance; that is, the current through the impedance does not faithfully follow the change in voltage. Various combinations of voltage and current for this particular nonlinear impedance may be obtained by use of this voltage-current curve. The series combination of a linear and a nonlinear impedance is illustrated in view (A) of figure 1-9. The voltage-current charts of Z1 and Z2 are shown in view (B). A chart of the combined impedance can be plotted by adding the amount of voltage required to produce a particular current through linear impedance Z1 to the amount of voltage required to produce the same amount of current through nonlinear impedance Z2. The total will be the amount of voltage required to produce that particular current through the series combination. For example, point a (25 volts) is added to point c (50 volts) which yields point e (75 volts); and point b (50 volts) is added to point d (100 volts) which yields point f (150 volts). Intermediate points may be determined in the same manner and the resultant characteristic curve (Z1 + Z2) is obtained for the series combination. Figure 1-9A.—Combined linear and nonlinear impedances. Figure 1-9B.—Combined linear and nonlinear impedances. You should see from this graphic analysis that when a linear impedance is combined with a nonlinear impedance, the resulting characteristic curve is nonlinear. Some examples of nonlinear impedances are crystal diodes, transistors, iron-core transformers, and electron tubes. Figure 1-10 illustrates an ac sine-wave generator applied to a circuit containing several linear impedances. A sine-wave voltage applied to linear impedances will cause a sine wave of current through them. The wave shape across each linear impedance will be identical to the applied waveform. Figure 1-10.—Sine wave generator applied to several impedances. The amplitude, on the other hand, may differ from the amplitude of the applied voltage. Furthermore, the phase of the voltage developed by any of the impedances may not be identical to the phase of the voltage across any of the other impedances or the phase of the applied voltage. If an impedance is a reactive component (coil or capacitor), voltage or current may lead or lag, but the wave shape will remain the same. In a linear circuit, the output of the generator is not distorted. The frequency remains the same throughout the entire circuit and no new frequencies are generated. View (A) of figure 1-11 illustrates a circuit that contains a combination of linear and nonlinear impedances with a sine wave of voltage applied. Impedances Z2, Z3, and Z4 are linear; and Z1 is nonlinear. The result of a linear and nonlinear combination of impedances is a nonlinear waveform. The curve Z, shown in view (B), is the nonlinear curve for the circuit of view (A). Because of the nonlinear impedance, current can flow in the circuit only during the positive alternation of the sine-wave generator. If an oscilloscope is connected, as shown in view (A), the waveform across Z3 will not be a sine wave. Figure 1-12, view (A), illustrates the sine wave from the generator and view (B) shows the waveform across the linear impedance Z3. Notice that the nonlinear impedance Z1 has eliminated the negative half cycles. Figure 1-11A.—Circuit with nonlinear impedances. Figure 1-11B.—Circuit with nonlinear impedances. Figure 1-12A.—Waveform in a circuit with nonlinear impedances. Figure 1-12B.—Waveform in a circuit with nonlinear impedances. The waveform in view (B) is no longer identical to that of view (A) and the nonlinear impedance network has generated HARMONIC FREQUENCIES. The waveform now consists of the fundamental frequency and its harmonics. (Harmonics were discussed in NEETS, Module 9, Introduction to Wave-Generation and Wave-Shaping Circuits.) A circuit composed of two sine-wave generators, G1 and G2, and two linear impedances, Z1 and Z2, is shown in figure 1-13. The voltage applied to Z1 and Z2 will be the vector sum of the generator voltages. The sum of the individual instantaneous voltages across each impedance will equal the applied voltages. Figure 1-13.—Two sine-wave generators with linear impedances. If the two generator outputs are of the same frequency, then the waveform across Z1 and Z2 will be a sine wave, as shown in figure 1-14, views (A) and (B). No new frequencies will be created. Relative amplitude and phase will be determined by the relative values and types of the impedances. Introduction to Matter, Energy, and Direct Current, Introduction to Alternating Current and Transformers, Introduction to Circuit Protection, Control, and Measurement Introduction to Electrical Conductors, Wiring Techniques, and Schematic Reading Introduction to Generators and Motors Introduction to Electronic Emission, Tubes, and Power Supplies, Introduction to Solid-State Devices and Power Supplies Introduction to Amplifiers, Introduction to Wave-Generation and Wave-Shaping Circuits Introduction to Wave Propagation, Transmission Lines, and Antennas Microwave Principles, Modulation Principles , Introduction to Number Systems and Logic Circuits, Introduction to Microelectronics, Principles of Synchros, Servos, and Gyros Introduction to Test Equipment Radio-Frequency Communications Principles Radar Principles, The Technician's Handbook, Master Glossary, Test Methods and Practices, Introduction to Digital Computers, Magnetic Recording, Introduction to Fiber Optics
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For potential Ph.D. students Over the next few years, I may take on a few additional Ph.D. students, although times may come when I'll be too full (e.g. a time that ended recently). This page is intended for those considering working with me, although it also contains some tips for graduate students in general, as well as an idea of what I expect. Algebraic geometry (or at least my take on it) is a technical subject that also requires a good deal of background in other subjects, as well as geometric intuition. So before I take you on as a new student, you should be comfortable with the foundations of the subject, which means having done the majority of the exercises in Hartshorne or my course notes, and being able to explain them on demand. (You shouldn't do this on your own; I'm happy talking with you through this process.) You should also be actively interested in learning about nearby subjects that interest you. Which subjects they are is up to you. If you're not interested in regularly attending talks, and being broadly interested in mathematics outside of your thesis topic, or if you don't feel like getting technical in a rather serious way, I'm probably not a good fit for you. If you are interested in some of the ideas of algebraic geometry, you should also consider a number of other advisors. In this department there are a good number of people interested either directly or indirectly in algebro-geometric ideas. You can read about them here. I will of course be happy to talk with you no matter whom you are working with. My personal style as an advisor I'll suggest problems to think about, starting from small toy problems (which have a habit of growing into interesting serious research). You'll have to pick what to work on, and find your own thesis problem. Mathematics isn't just about answering questions; even more so, it is about asking the right questions, and that skill is a difficult one to master. I like to meet my students every week (except for exceptional weeks, of which there are many). You may prefer not to meet in a given week if you have nothing much to report, but those weeks are particularly important to meet. The disadvantage of being a student of a young parent is that you'll have to be prepared to be more independent. I will be a demanding advisor, more demanding than most. I have pretty broad interests in and near algebraic geometry. To get an idea of the things I think about, see some of the things I've written. However, some of those subjects may not be ideal for a Ph.D. student for a number of reasons. I'm interested in lots of things. I may however not be the ideal person to supervise lots of things. For example, I will not supervise a thesis in a nearby field. But I definitely do not require that you work on problems directly related to my own research. General advice (which would apply particularly to my own students) Think actively about the creative process. A subtle leap is required from undergraduate thinking to active research (even if you have done undergraduate research). Think explicitly about the process, and talk about it (with me, and with others). For example, in an undergraduate class any Ph.D. student at Stanford will have tried to learn absolutely all the material flawlessly. But in order to know everything needed to tackle an important problem on the frontier of human knowledge, one would have to spend years reading many books and articles. So you'll have to learn differently. But how? Don't be narrow and concentrate only on your particular problem. Learn things from all over the field, and beyond. The facts, methods, and insights from elsewhere will be much more useful than you might realize, possibly in your thesis, and most definitely afterwards. Being broad is a good way of learning to develop interesting questions. When you learn the theory, you should try to calculate some toy cases, and think of some explicit basic examples. Talk to other graduate students. A lot. Organize reading groups. Also talk to post-docs, faculty, visitors, and people you run into on the street. I learn the most from talking with other people. Maybe that's true for you too. On seminars: • Older graduate students will verify that there is a high correlation between those students who are doing the broadest and deepest work and those who are regularly attending seminars. Many people erroneously conclude that those who are the strongest students therefore go to seminars, while in fact the causation goes very much in the opposite direction. • Go to research seminars earlier than you think you should. Do not just go to seminars that you think are directly related to what you do (or more precisely, what you currently think you currently do). You should certainly go to every single seminar related to algebraic geometry that you can, and likely drop by other seminars occasionally too. Learning to get information out of research seminars is an acquired skill, usually acquired much later than the skill of reading mathematics. You may think it isn't helpful to go to a seminar where you understand just 5% of what the speaker says, and may want to wait until you are closer to 100%; but no one is anywhere near 100% (even the speaker!), so you should go anyway. • Try to follow the thread of the talk, and when you get thrown, try to get back on again. (This isn't always possible, and admittedly often the fault lies with the speaker.) • At the end of the talk, you should try to answer the questions: What question(s) is the speaker trying to answer? Why should we care about them? What flavor of results has the speaker proved? Do I have a small example of the phenonenon under discussion? You can even scribble down these questions at the start of the talk, and jot down answers to them during the talk. • Try to extract three words from the talk (no matter how tangentially related to the subject at hand) that you want to know the definition of. Then after the talk, ask me what they mean. (In general, feel free to touch base with me after every seminar. I might tell you something interesting related to the talk.) • New version of the previous jot: try the "three things" exercise. • See if you can get one lesson from the talk (broadly interpreted). If you manage to get one lesson from each talk you go to, you'll learn a huge amount over time, although you'll only realize this after quite a while. (If you are unable to learn even one thing about mathematics from a talk, think about what the speaker could have done differently so that you could have learned something. You can learn a lot about giving good talks by thinking about what makes bad talks bad.) • Try to ask one question at as many seminars as possible, either during the talk, or privately afterwards. The act of trying to formulating an interesting question (for you, not the speaker!) is a worthwhile exercise, and can focus the mind. • Here's a phenomenon I was surprised to find: you'll go to talks, and hear various words, whose definitions you're not so sure about. At some point you'll be able to make a sentence using those words; you won't know what the words mean, but you'll know the sentence is correct. You'll also be able to ask a question using those words. You still won't know what the words mean, but you'll know the question is interesting, and you'll want to know the answer. Then later on, you'll learn what the words mean more precisely, and your sense of how they fit together will make that learning much easier. The reason for this phenomenon is that mathematics is so rich and infinite that it is impossible to learn it systematically, and if you wait to master one topic before moving on to the next, you'll never get anywhere. Instead, you'll have tendrils of knowledge extending far from your comfort zone. Then you can later backfill from these tendrils, and extend your comfort zone; this is much easier to do than learning "forwards". (Caution: this backfilling is necessary. There can be a temptation to learn lots of fancy words and to use them in fancy sentences without being able to say precisely what you mean. You should feel free to do that, but you should always feel a pang of guilt when you do.) • Your thesis problem may well come out of an idea you have while sitting in a seminar. • Go to seminar dinners when at all possible, even though it is scary, and no one else is going. • Go to colloquia fairly often, so you have a reasonable idea of what is happening in other parts of mathematics. It is amazing what can become relevant to your research. You won't believe it until it happens to you. And it won't happen to you unless you go to colloquia. Ditto for seminars in other fields. On giving talks Here's a great story from Mark Meckes that simultaneously illustrates a number of points. By chance, I recently saw a PhD thesis whose acknowledgements ended with the sentence "Finally, I would like to thank Dr. Mark Meckes, whose talk in Marseille in May of this year [2008] provided the final insight I needed to completely answer Kuperberg's Conjecture." What is interesting about this is that not only had I never heard of Kuperberg's Conjecture, but my talk was completely unrelated to the subject of the thesis, and even after reading the relevant section of the thesis I still couldn't see the connection. So one truly never knows where useful insights will come from. One of the many things I love about this story is that I don't find it at all surprising! So go to talks --- and give talks --- and talk to people! On writing: • For people writing research papers for the first time (or not for the first time), here is a lecture by Serre, one of the best mathematical writers of all time, with some opinions on good (and bad) writing. • Terry Tao on writing. When thinking about advisors, talk to past and current graduate students. (My former and current students: Eric Katz 2004, Rob Easton 2007, Andy Schultz 2007, Jarod Alper 2008, Joe Rabinoff 2009, Nikola Penev 2009, Jack Hall 2010, Dung Nguyen 2010, Atoshi Chowdhury, Yuncheng Lin, Daniel Litt. I also collaborated with Kirsten Wickelgren 2009, who worked with Gunnar Carlsson.) Advice from others: Specific advice about algebraic geometry at Stanford Sign up for the algebraic geometry mailing list. Go to the Western Algebraic Geometry Seminar, a twice-yearly conference. Occasionally go to Berkeley when you hear about something particularly interesting. When you are up to it, subscribe to the daily mailing of abstracts of algebraic geometry papers posted to the arXiv. Then most days, just delete them, but when you have some time, browse through them, and read the abstracts that catch your eye. You'll gradually get a sense of what is going on in the field. Caution: this can be psychologically damaging, as you'll feel "here I am stuck on this simple problem, and thousands of papers are coming out...". So only do this if and when you're ready. I might delete this paragraph at some point if I realize it is counterproductive. (Thanks to many people for advice about this page, including Yvonne Lai, Daniel Erman, and Mark Meckes.) Return to my homepage
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Compactness of the class of connected sets with perimetre smaller than 1? up vote 8 down vote favorite It is my first post, so please be indulgent! Here is the problem: I am in the class S of closed subsets of [0,1]^2 that are connected and have perimeter less or equal to 1. I endow this space with the Hausdorff metric (or equivalently Fell topology), that says that for two compacts A, B, d(A,B)<=r iff every point of A is at distance less than r of B, and the other way Question: Is this space compact? Equivalent question: Is the function "perimeter" lower semi continuous on this set? (It is equivalent because the Hausdorff metric is compact for the class of all compact sets, and the class of connected sets is closed). In other words, given a sequence of connected sets with perimeter at most 1, is it possible to see suddenly some perimeter appear at the limit? (which would be an answer "no" to the question). The perimeter here is the 1-dimensional measure of the boundary, i.e. the infimum over all coverings of the boundary by balls of the sum of the diameters of the balls. Remark: If one drops the assumption of connectedness, it is not true anymore (consider for instance a set of points -thus with zero perimeter- that becomes dense in the square). So this assumption is very important! Thak you in advance! Hi Remark: I don't know the answer to your question, but here's a potential strategy. As Tom Leinster has been explaining for some time now (see eg his posts on n-Category Cafe), another good definition of perimeter of a closed set $X$ is $\frac{\partial}{\partial\epsilon} \bigr|_{\epsilon=0} \mathrm{Vol}(X_\epsilon)$, where $X_\epsilon$ is the set of all points within distance ϵ of X. Perhaps this is the same as your definition. Anyway, then perhaps you can successfully swap a limit somewhere when computing a limit in Hausdorff topology. – Theo Johnson-Freyd Aug 3 '11 at 19:06 add comment 1 Answer active oldest votes No. Let $B$ be a closed ball of radius 1/2 and $I$ a diameter of $B$. Construct a Cantor-like set $K\subset I$ of lengths $\mathcal H^1(K)=0.9$ (where $\mathcal H^1$ denotes the 1-dimensional Hausdorff measure). We have $I\setminus K=\bigcup I_i$ where $I_1,I_2,\dots$ are disjoint open subintervals of $I$ and $\sum_{i=1}^\infty\mathcal H_1(I_i)=0.1$. Let $B_i$ be the open ball for which $I_i$ is a diameter, and let $X_k=B\setminus\bigcup_{i=1}^k B_i$. Then each $X_k$ is a closed connected set and the sequence $\{X_k\}$ Hausdorff converges to $X=\bigcap_{k=1}^\infty X_k=B\setminus\bigcup_{i=1}^\infty B_i$. up vote 12 The boundary of $X_k$ is a union of $k+1$ disjoint circles $\partial B$ and $\partial B_i$, $1\le i\le k$, hence $$ \mathcal H^1(\partial X_k) = \mathcal H^1(\partial B)+\sum_{i=1}^k \ down vote mathcal H^1(\partial B_i) = \pi+\sum_{i=1}^k\pi\mathcal H^1(I_i) \le \pi+0.1\pi =: C. $$ However the boundary of $X$ contains $K$, hence $\mathcal H^1(\partial X)\ge\mathcal H^1(\ accepted partial B)+\mathcal H^1(K)=\pi+0.9> C$. Thus the space of connected sets of perimeter $\le C$ is not closed. Nice example. It might be interesting to notice that when you consider a subset of the boundary with the Cantor set is removed, the result is true. See R. Cerf, The Hausdorff Lower Semicontinuous Envelope Of The Length In The Plane Ann. Scuola Norm. Sup. Pisa Cl. Sci. (5) I (2002), 33$-$71. archive.numdam.org/ARCHIVE/ASNSP/ASNSP_2002_5_1_1/… – Tapio Rajala Aug 4 '11 at 9:51 Very nice example (I actually believed the answer would be yes), Cantor sets are even more vicious than I thought. Thank you very much! – Raphael L Aug 5 '11 at 8:25 add comment Not the answer you're looking for? Browse other questions tagged gt.geometric-topology or ask your own question.
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Image self consistency from xkcd I love xkcd. A comic combining fun and math by definition has to be good and geeky and the author, Randall Munroe, is a real genius on this. The latest comic is pretty interesting The image is self-descriptive, meaning that each graph represents information about the image itself. For example, the first panel contains a pie chart which says how many pixels are either white or black on the image. Clearly, the relative amount of black pixels in the image depends on the size of the slice of that piechart representing the amount of black pixels, a “chicken-egg” kind of problem. It is apparently difficult to obtain such image, because the plotted data must be consistent with themselves via the graphical representation. This kind of problems, where the solution depends on itself, is quite common in many scientific problems, and it’s solved through self-consistency. The trick is as follows: we start with a first, approximate solution, called a guess, and we apply a method that gives us a result depending on this guess. Then, we take this newly obtained result, and reapply the method again, to obtain a new result, and then again, and again, until, hopefully, the input and the output of the method are the same. When this occurs, we solved our problem via self-consistency. Of course, this convergence is not guaranteed to occur, but if it occurs, we found a solution (there could be more than one). Let’s see it in action in a simplified form. I wrote two small python programs. They use matplotlib and the Python Image Library. The first (called piechart.py) creates a pie chart from a given data import sys from matplotlib import pyplot white = int(sys.argv[1]) black = int(sys.argv[2]) pyplot.pie([white, black], colors=('w', 'k')) pyplot.savefig(sys.argv[3], format="pdf") If we call this program specifying two values (the absolute values are not important, as the pie chart shows relative amount), it draws the pie chart accordingly: python piechart.py 100 400 piechart_100w_400b.pdf convert -geometry 210x158 piechart_100w_400b.pdf piechart_100w_400b.png This creates a pie chart where white is 1/5 of the pie chart area and black is 4/5. Please note that due to a setup problem of my matplotlib I can only create pdf, so I convert the pdf into png of defined size, in our case, 210×158, using the convert program. The total size of the image is of course important, having an influence on the total number of pixels. I chose a good value for presentation purposes which guarantees quick convergence. The second program is called imagedata.py and extracts size and number of white and black pixels from an image. import sys from PIL import Image im = Image.open(sys.argv[1]) white = 0 black = 0 for i in im.getdata(): if i == (255,255,255): white += 1 # we assume black everything that is not white: black += 1 print im.size[0],im.size[1],white,black If we run this program on the png image, it will tell us how many pixels are white, and how many are black. $ python imagedata.py piechart_100w_400b.png Of the 33.180 pixels defining the full image above (border included, not only the pie chart circle), 23988 are white (72%), and 9192 are black (28%). Hence the image is not representing itself: the plot represents our initial values of 20 % white and 80 % black. Now we create a new image, in agreement with the iterative procedure, passing the most recently obtained values python piechart.py 23988 9192 piechart_23988w_9192b.pdf convert -geometry 210x158 piechart_23988w_9192b.pdf piechart_23988w_9192b.png and repeat the process. This becomes tedious very soon, so I wrote a driver (driver.sh) to perform the process for me # generates the starting guess python piechart.py 100 400 iter_0.pdf convert -geometry 210x158 iter_0.pdf iter_0.png # iterative process echo "step w h white black" while true; data=`python imagedata.py iter_$(($step-1)).png` echo "$step - $data" python piechart.py `echo $data|awk '{print $3}'` `echo $data|awk '{print $4}'` iter_$step.pdf convert -geometry 210x158 iter_$step.pdf iter_$step.png If we run it, we immediately see a very interesting result: step w h white black 1 - 210 158 23988 9192 2 - 210 158 29075 4105 3 - 210 158 30551 2629 4 - 210 158 30977 2203 5 - 210 158 31108 2072 6 - 210 158 31158 2022 7 - 210 158 31164 2016 8 - 210 158 31169 2011 9 - 210 158 31172 2008 10 - 210 158 31172 2008 11 - 210 158 31172 2008 12 - 210 158 31172 2008 The number of black pixels decreases, and the number of white ones increases. At every step, the image slightly changes, until it reaches a point where it does not change anymore: it achieved self-consistency, and it is representing itself. This is a movie of the various steps until convergence What if we started from the other direction, namely, with a guess containing zero as the number of black pixels? The result would have been the same 1 - 210 158 31750 1430 2 - 210 158 31320 1860 3 - 210 158 31221 1959 4 - 210 158 31184 1996 5 - 210 158 31178 2002 6 - 210 158 31174 2006 7 - 210 158 31172 2008 8 - 210 158 31172 2008 9 - 210 158 31172 2008 Again, even with a different starting guess, we obtain the same result, here depicted as a movie I hope this gave a brief explanation on how Randall achieved the self-consistent image. His case was more complex, having three plots. Also, the comic is scribbled, so either he drew it by hand, approximating the computed result, or he performed some scribble-like transformation preserving the pixel count. I assume it is the former.
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MathGroup Archive: April 2010 [00069] [Date Index] [Thread Index] [Author Index] Re: Combining elements of a list • To: mathgroup at smc.vnet.net • Subject: [mg108850] Re: Combining elements of a list • From: Murray Eisenberg <murray at math.umass.edu> • Date: Sun, 4 Apr 2010 07:44:11 -0400 (EDT) I'm going to assume you don't really have symbols (t, h, etc.) but rather one-letter strings ("t", "h", etc.) here. The basic function you want is StringJoin. Thus: StringJoin[{"t", "h", "i", "s"}] Next, you have your list of lists: lis = {{"t", "h", "i", "s"}, {"i", "s"}, {"a"}, {"t", "e", "s", "t"}}; (I left out the last word.) So Map the function StringJoin onto that at level 1: Map[StringJoin, lis, 1] {"this", "is", "a", "test"} Now you need to append a blank to each word (except the last). For a single string str StringInsert[str," ",-1] does it, as in: trial=StringInsert["this"," ",-1] (* you can't see the trailing blank here, so... *) (You could also use StringJoin instead of StringInsert.) Now Map that function of appending a blank onto the list of words: appended = Map[StringInsert[#, " ", -1] &, words] {this ,is ,a ,test } Same thing, abbreviated: StringInsert[#, " ", -1] & /@ words Finally, join all the individual (blank-trailed) words into a single string and delete the final trailing blank: Obviously, all those steps could be combined, encapsulated into a single sentenceFromLetters[lis_] := StringJoin[StringInsert[#, " ", -1] & /@ Map[StringJoin, lis, 1]] Doubtless there are terser, or at least alternative ways, to do this using pattern-matching for at least some of the steps. If your original list really consisted of lists of symbols rather than lists of one-character strings, you could first convert that to a list of lists of one-character strings by using ToString. On 4/3/2010 7:09 AM, ebaugh at illinois.edu wrote: > How could I go from: > {h,e,l,l,o} > to > {hello}? > That is the first step of what I am really looking to do. Which is > to go from: > {{t,h,i,s},{i,s},{a},{t,e,s,t},{m,e,s,s,a,g,e}} > to > "this is a test message" > Thanks all, > Jason Ebaugh Murray Eisenberg murray at math.umass.edu Mathematics & Statistics Dept. Lederle Graduate Research Tower phone 413 549-1020 (H) University of Massachusetts 413 545-2859 (W) 710 North Pleasant Street fax 413 545-1801 Amherst, MA 01003-9305
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Dominoes program... HELP PLEASE! 04-27-2010, 11:51 PM Dominoes program... HELP PLEASE! I have attached the assignment given by my professor. I'm just a little confused. I can't develop and algorithm for this. I know I need a 2-D array for the board, but I don't know how to fill it and then rearrange the Dominoes to find the number of different ways to fill the board. If I'm not clear just tell me and I will clarify. 04-27-2010, 11:55 PM my file didn't attach so here it is: CSCE 1040.001/.002 Program # 4, 100 points Due: April 30, 2010 at 10:00pm. You are to write a Java method which will count the number of different ways that a 3xN board can be completely filled with dominos (a domino is 1x2). Completely, in this case, means there are no unfilled cells in the board. The best way to fill the board is to fill columns left-to-right using recursion (see Chapter 11 of the text). The value of N (N>1) will be passed to your program via Dominoes may be placed horizontally or vertical. At any position, both possible domino placements should be tried. I.e – placing a domino horizontally. Your program (main) is to call the method defined above and produce one number, the number of possible ways to completely fill a 3xN board, with appropriate formatting and description, of course. Also, your program should contain appropriate comments. Submit a single java file via Blackboard. There are three ways to completely fill a 3 x 2. There are zero ways to completely fill a 3 x 3. The board can be a 2-dimentional integer array. Your program must work for any value of N (N>1). Therefore you must allocate memory for any arrays dynamically, either in main or inside of a I strongly recommend that you write a printBoard method to help you with debugging. A good way to keep track of dominoes (mark them on the board) is to number them sequentially and to print them out mod 10. Thus, the first solution of the 3x3 would be printed as One possible way to split up the work would be to write the two methods. 1. tryHorizontal(row, col) which would try to place a domino horizontally at board[row, col] and board[row, col+1], checking, of course, for conditions like board position already filled, placing part of a domino outside of the board, etc. 2. and tryVertical(row, col) which would try to place a domino vertically. These two methods would be used inside of a method tryRowCol(row, col). public tryRowCol( int row, int col){ if (.…) tryHorizontal(row, col); if (…..) tryVertical(row, col); } // end tryRowCol
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188 helpers are online right now 75% of questions are answered within 5 minutes. is replying to Can someone tell me what button the professor is hitting... • Teamwork 19 Teammate • Problem Solving 19 Hero • Engagement 19 Mad Hatter • You have blocked this person. • ✔ You're a fan Checking fan status... Thanks for being so helpful in mathematics. If you are getting quality help, make sure you spread the word about OpenStudy. This is the testimonial you wrote. You haven't written a testimonial for Owlfred.
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Smooth Differential Graded Algebra? Posted by Urs Schreiber A while ago I had a discussion with Todd Trimble about how to define “generalized smooth” differential graded-commutative algebras (DGCAs), generalizing the “generalized smooth”-algebras, called $C^\ infty$-algebras, discussed in the book by Moerdijk & Reyes. I think back then we fell short of arriving at a satisfactory conclusion. As I mentioned, I would like to pick up that thread again and chat about some ideas. This here is the general motivation: given a category $S$ of “test objects”, generalized spaces are presheaves on $S$, namely things that can be probed by throwing objects of $S$ into them, and generalized quantities (to be thought of as numbers, functions, sections, etc. as discussed in more detail below) are co-presheaves on $S$. If $S := CartesianSpaces$ is the full subcategory of Manifolds on the manifolds $\mathbb{R}^n$, for all $n \in \mathbb{N}$, then the spaces in question are something like “smooth spaces” (in particular, if their underlying presheaves happen to be concrete sheaves, these these are diffeological or Chen-smooth spaces) and then the quantities are something like “smooth quantities” (in particular, if the underlying co-presheaves happen to be monoidal, these are those $C^\infty$-algebras). Given such a notion of spaces, there is an obvious notion of higher spaces: pick your favorite definition of $\infty$-groupoid. Then a higher degree space, an $\infty$-space, should be an $\infty$ -groupoid internal to the above spaces. What is the analog of this on the side of “quantities”? What is an $\infty$-quantity? There are several possible answers one could come up with, I suppose, such as the answer by David Spivak, who replaces co-presheaves by simplicial co-presheaves and hence essentially follows the above $\infty$-ization of spaces. But here I am interested in a different kind of answer which supposes that $\infty$-quantities corresponding to $\infty$-spaces in the above sense are something like “quasi-free differential graded commutative $C^\infty$-algebras” , $C^\infty$qDGCAs – to be be determined. There is a reason for this assumption, namely $\infty$-Lie theory, but that is not of concern right now. Here I just want to talk about possible definitions of $C^\infty$-qDGCAs, an interesting question in its own right. The idea I want to propose is simple. The goal is to have it “as simple as possible but no simpler”. Maybe you can help me check if that’s achieved, especially concerning the “no simpler”-part (i.e. the mistakes). Here goes: Write $Quantities := Set^{CartesianSpaces}$ for the category of co-presheaves on CartesianSpaces. As a co-presheaf category, this is a monoidal category with tensor product of $A,B \in Quantities$ given by $A \times B : \mathbb{R}^k \mapsto A(\mathbb{R}^k) \times B(\mathbb{R}^k) \,.$ In any monoidal category we can consider monoids: Write $Algebras := Monoids(Quantities)$ for the category of monoids internal to Quantities. Every $C^\infty$-algebra of Moerdijk-Reyes canonically becomes an object of Algebras by using postcomposition with the maps $\cdot^k : \mathbb{R}^k \times \mathbb{R}^k \to \mathbb{R}^k$ of componentwise multiplication in $\mathbb{R}$. Write $Spaces := Sheaves(CartesianSpaces)$ for the category of sheaves on CartesianSpaces. For every $X \in Spaces$ we get an object $C^\infty(X) \in Algebras$, the algebra of functions whose underlying co-presheaf is $C^\infty(X) : \mathbb{R}^k \mapsto Hom_{Spaces}(X, \mathbb{R}^k)$ and whose monoidal structure comes from postcomposition with the $\cdot^k$ from above: $Hom(X, \mathbb{R}^ k) \times Hom(X, \mathbb{R}^k) \stackrel{\simeq}{\to} Hom(X, \mathbb{R}^k \times \mathbb{R}^k) \stackrel{Hom(-,\cdot^k)}{\to} Hom(X, \mathbb{R}^k) \,.$ For $X$ an ordinary manifold, $C^\infty(X)$ is its ordinary algebra of smooth functions. Now comes the point: Since the $Algebras$ above are monoid objects, we can consider modules internal to $Quantities$ of objects in $Algebras$. (In fact, there should be a monoidal bicategory $Bimod Let $E \to X$ be a vector bundle internal to $Spaces$ and consider the set $Sections(E) \in Sets$ of its sections. The assignment $\Gamma(E) : \mathbb{R}^k \mapsto Sections(E \otimes \mathbb{R}^k)$ extends naturally to a co-presheaf on $CartesianSpaces$, hence to an object in $Quantities$. This naturally comes with an action of $C^\infty(X) \in Algebras$, where in components the action is given by postcomposition with $\cdot^k$ acting on the trivial bundle part: $\array{ Hom(X,\mathbb{R}^k) \times Sections(E \otimes \mathb{R}^k) \\ \downarrow^{\subset} \\ Hom(X,\mathbb{R}^k) \times Hom(X,E \otimes \mathbb{R}^k) \\ \downarrow^\simeq \\ Hom(X,( E \otimes \mathbb{R}^k) \times \mathbb{R}^k ) \\ \downarrow \\ Hom(X,E \otimes \mathbb{R}^k) }$ For $C \in Quantities$ an $(A \in Algebras)$-module, There is the obvious notion of dual-over-$A$ module $C^* := Hom_{A-Modules}(C,A)$. Using all this, the standard definition of qDGCAs should now straightforwardly generalize to the generalized smooth context: Definition: A quasi-free differential graded-commutative algebra (qDGCA) over $A \in Algebras$ is a non-positively graded cochain complex $V$ of $A$-modules internal to $Quantities$ together with a degree +1 differential $d : \wedge^\bullet_A V^* \to \wedge^\bullet_A V^*$. I am thinking that all the ingredients I glossed over here have the obvious straightforward definition. But maybe I should check this in more detail. (One might want to add to the above definition the condition that $V$ is degree-wise projective.) Posted at September 9, 2008 9:33 AM UTC Re: Smooth Differential Graded Algebra? How does Lawvere’s treatment of intensive and extensive quantities fit with what you’re saying? Posted by: David Corfield on September 9, 2008 12:07 PM | Permalink | Reply to this Re: Smooth Differential Graded Algebra? Lawvere’s treatment of intensive and extensive quantities So, from p. 14, we have “extensive quantity” = homology cycles “intensive quantitiy” = cohomology cocycle On page 15 Grassman’s “extensive quantities” are mentioned. Now, that’s interesting, since these are of course the elemens of a Grassman algbra $\wedge^\bullet V$ which play a central role in the “$C ^\infty qDGCAs$” mentioned above. Still reading… Posted by: Urs Schreiber on September 9, 2008 12:29 PM | Permalink | Reply to this Re: Smooth Differential Graded Algebra? Perhaps a candidate for a tac reprint. It would be nice to know what happens on pp. 18-19 and pp. 25-26. Posted by: David Corfield on September 9, 2008 12:33 PM | Permalink | Reply to this Re: Smooth Differential Graded Algebra? I did some searching. If I understand correctly then an “intensive quantity” is taken to be essentially one that depends contravariantly on Spaces, while an “extensive quantity” is essentially one that depends covariantly. So function algebras, $C^\infty : Spaces \to Algebras$ is an intensive quantity, while linear duals of such (distributions) are “extensive”. I must admit that I haven’t figured out yet in which sense the words “intensive” and “extensive” are supposed to be suggestive here. But in any case I suppose I can now answer your question: the quantities I was talking about in the above entry are “intensive”, in this sense (essentially being functions and sections on spaces). Posted by: Urs Schreiber on September 9, 2008 12:50 PM | Permalink | Reply to this Re: Smooth Differential Graded Algebra? A classic example of the difference between intensive and extensive properties is mass (extensive) and density (intensive). Intensive quantities work well with products via projection. Extensive quantities work well with coproducts via sum. Posted by: David Corfield on September 9, 2008 1:20 PM | Permalink | Reply to this Re: Smooth Differential Graded Algebra? Is it an issue that normally one thinks of multiplying an intensive quantity by an extensive quantity to yield an extensive quantity (density $\times$ volume = mass or integrating a density against a measure), where you are multiplying intensive quantities? Posted by: David Corfield on September 10, 2008 2:25 PM | Permalink | Reply to this
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Rebuilding the Tower of Hanoi The Tower of Hanoi is a puzzle that consists of three pegs and a set of disks. Each disk has a different diameter and a hole in the middle so that the disk can fit onto any of the pegs. The initial puzzle setup has two of the pegs empty and all the disks on the third peg (source) in monotonically decreasing order of diameter from bottom to top, which forms a structure that is reminiscent of a tower. The goal of the puzzle is to move the tower from the source peg to a specified peg (destination) using the other peg to temporarily hold disks. The two rules of the Tower of Hanoi puzzle are that only one disk at a time can be moved from the top of a stack of disks on a peg to some other peg, and disks with larger diameter cannot be placed on top of smaller diameter disks. French mathematician Edouard Lucas developed the puzzle in 1883. He also created the myth for his puzzle that claimed monks have been working non-stop on a 64-disk version from the beginning of time. Once they have solved this problem, the tower will crumble and the world will end. It's a good story and, I'm sure, it helped to promote the puzzle, but everyone knows that the world ends at 03:14:07 on Tuesday, January 19, 2038. A programmed solution can be implemented using recursion in a most elegant way. (Again with the recursion? Just one more to finish up, I swear. I'll start my next post with something completely different.) Here's one way to code up a solution. void tower(char source, char dest, char temp, int level) if (level > 0) { tower(source, temp, dest, level-1); printf("Move from %c to %c\n", source, dest); tower(temp, dest, source, level-1); printf("Move from %c to %c\n", source, dest); . . . tower('A', ‘C', 'B', numDisks-1); . . . I've used single characters to denote the pegs ('A' is the initial source peg, 'C' is the final destination, and 'B' is the temporary peg). The recursion is halted when the level parameter reaches zero. This corresponds to the source peg having one disk remaining on it, so the code simply prints the move of a disk from the source to the destination peg without further recursive calls. As you can see, the purpose of the code is to print out the set of instructions that can be mechanically followed by someone trying to solve the puzzle in the fewest moves.
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Math Forum Discussions - geometry.college.independent Discussion: geometry.college.independent A discussion of topics covered in college geometry, problems appropriate for that level, and geometry education. To subscribe, send email to majordomo@mathforum.org with only the phrase subscribe geometry-college in the body of the message. To unsubscribe, send email to majordomo@mathforum.org with only the phrase unsubscribe geometry-college in the body of the message. Posts to this group from the Math Forum do not disseminate to usenet's geometry.college newsgroup.
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Patent application title: SORTING A DATASET OF INCREMENTALLY RECEIVED DATA Inventors: Jeremy Eric Elson (Seattle, WA, US) Edmund Bernard Nightingale (Redmond, WA, US) Owen Sebastian Hofmann (Austin, TX, US) Assignees: Microsoft Corporation IPC8 Class: AG06F1730FI USPC Class: 707752 Class name: Publication date: 2012-12-27 Patent application number: 20120330979 Sign up to receive free email alerts when patent applications with chosen keywords are published SIGN UP A method of sorting a dataset includes incrementally receiving data from the dataset, and incrementally storing the received data as individual input data subsets as the data is received, thereby sequentially generating a plurality of filled data subsets of unsorted data. The method includes individually sorting each filled data subset of unsorted data concurrently with receiving data for a next one of the individual input data subsets, thereby sequentially generating a plurality of sorted input data subsets, and performing a merge sort on the plurality of sorted input data subsets, thereby incrementally generating a sorted version of the dataset. A method of sorting a dataset, comprising: incrementally receiving data from the dataset; incrementally storing the received data as individual input data subsets as the data is received, thereby sequentially generating a plurality of filled data subsets of unsorted data; individually sorting each filled data subset of unsorted data concurrently with receiving data for a next one of the individual input data subsets, thereby sequentially generating a plurality of sorted input data subsets; and performing a merge sort on the plurality of sorted input data subsets, thereby incrementally generating a sorted version of the dataset. The method of claim 1, wherein the sorted version of the dataset includes a plurality of sequentially generated sorted output data subsets, and wherein the method further comprises: outputting each of the sorted output data subsets concurrently with generating a next one of the sorted output data subsets. The method of claim 2, wherein the sorted output data subsets each have a same size as the individual input data subsets. The method of claim 2, wherein the outputting each of the sorted output data subsets comprises outputting each of the sorted output data subsets to a storage medium. The method of claim 2, wherein the outputting each of the sorted output data subsets comprises outputting each of the sorted output data subsets to a network file system. The method of claim 1, and further comprising: varying a size of the individual input data subsets based on a size of the dataset. The method of claim 1, wherein the individual input data subsets each have a size that is a predetermined fraction of a size of the dataset. The method of claim 1, wherein the dataset is stored as a plurality of portions on a plurality of computing devices, and wherein the data from the dataset is incrementally received from the plurality of computing devices. The method of claim 1, wherein the individually sorting each filled data subset of unsorted data is performed using a quick-sort algorithm. The method of claim 1, wherein the data incrementally received from the dataset is received from a storage medium. The method of claim 1, wherein the data incrementally received from the dataset is received from a network file system. A computer-readable storage medium storing computer-executable instructions that when executed by at least one processor cause the at least one processor to perform a method of sorting a dataset, the method comprising: incrementally receiving data from the dataset; sequentially generating a plurality of filled data subsets by incrementally storing the received data as individual input data subsets as the data is received; sequentially generating a plurality of sorted input data subsets by individually sorting each filled data subsets concurrently with receiving data for a next one of the individual data subsets; and incrementally generating a sorted version of the dataset by performing a merge sort on the plurality of sorted input data subsets. The computer-readable storage medium of claim 12, wherein the sorted version of the dataset includes a plurality of sequentially generated sorted output data subsets, and wherein the method further comprises: outputting each of the sorted output data subsets concurrently with generating a next one of the sorted output data subsets. The computer-readable storage medium of claim 13, wherein the sorted output data subsets each have a same size as the individual input data subsets. The computer-readable storage medium of claim 12, wherein the method further comprises: varying a size of the individual input data subsets based on a size of the dataset. The computer-readable storage medium of claim 12, wherein the individual input data subsets each have a size that is a predetermined fraction of a size of the dataset. The computer-readable storage medium of claim 12, wherein the dataset is stored as a plurality of portions on a plurality of computing devices, and wherein the data from the dataset is incrementally received from the plurality of computing devices. The computer-readable storage medium of claim 12, wherein the individually sorting each filled data subsets is performed using a quick-sort algorithm. The computer-readable storage medium of claim 12, wherein the filled data subsets have a non-uniform size. A method of sorting a dataset, comprising: incrementally receiving data from the dataset; sequentially generating a plurality of filled data subsets by incrementally storing the received data as individual input data subsets as the data is received; sequentially generating a plurality of sorted input data subsets by individually sorting each filled data subset concurrently with receiving data for a subsequent one of the individual input data subsets; incrementally generating a sorted version of the dataset by performing a merge sort on the plurality of sorted input data subsets, wherein the sorted version of the dataset includes a plurality of sequentially generated sorted output data subsets; and outputting each of the sorted output data subsets concurrently with generating a subsequent one of the sorted output data subsets. BACKGROUND [0001] Sorting a large dataset is a problem commonly found in many applications. The total time required to sort a large dataset can be split into two parts: first, the input/output (I/O) delay in reading all the unsorted data from stable storage (e.g., disk) and writing the sorted data back. Second, there are CPU requirements for comparing enough of the data elements sufficiently to sort them. The I/O portion of the sorting process is typically much slower than computation, particularly if the amount of computation done per unit of data is small. The time to sort data tends to be dominated by the time it takes to read or write the data from or to either the network or the storage medium (e.g. disk). This has changed in some recent storage systems, where I/O is dramatically faster than in previous systems--often by an order of magnitude. When sorting is implemented on such systems, the time required for computation becomes more significant, and it becomes more significant to optimize this portion of the sorting process. SUMMARY [0003] This summary is provided to introduce a selection of concepts in a simplified form that are further described below in the Detailed Description. This summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used to limit the scope of the claimed subject matter. One embodiment is directed to system that splits unsorted input data into smaller subsets as it arrives, and sorts each input subset while the subsequent input subset is being read (or received, in the case of a network file system). The system according to one embodiment performs a merge sort on the sorted subsets once the output stage begins, and performs a merge to produce an output subset while the previous output subset is being written (or transmitted, in the case of a network file system). One embodiment is directed to a method of sorting a dataset, which includes incrementally receiving data from the dataset, and incrementally storing the received data as individual input data subsets as the data is received, thereby sequentially generating a plurality of filled data subsets of unsorted data. The method includes individually sorting each filled data subset of unsorted data concurrently with receiving data for a next one of the individual input data subsets, thereby sequentially generating a plurality of sorted input data subsets, and performing a merge sort on the plurality of sorted input data subsets, thereby incrementally generating a sorted version of the dataset. BRIEF DESCRIPTION OF THE DRAWINGS [0006] The accompanying drawings are included to provide a further understanding of embodiments and are incorporated in and constitute a part of this specification. The drawings illustrate embodiments and together with the description serve to explain principles of embodiments. Other embodiments and many of the intended advantages of embodiments will be readily appreciated, as they become better understood by reference to the following detailed description. The elements of the drawings are not necessarily to scale relative to each other. Like reference numerals designate corresponding similar parts. FIG. 1 is a block diagram illustrating a computing environment suitable for implementing aspects of a system for sorting a dataset according to one embodiment. FIG. 2 is a block diagram illustrating a system for sorting a dataset according to one embodiment. FIG. 3 is a flow diagram illustrating a method of sorting a dataset according to one embodiment. DETAILED DESCRIPTION [0010] In the following Detailed Description, reference is made to the accompanying drawings, which form a part hereof, and in which is shown by way of illustration specific embodiments in which the invention may be practiced. It is to be understood that other embodiments may be utilized and structural or logical changes may be made without departing from the scope of the present invention. The following detailed description, therefore, is not to be taken in a limiting sense, and the scope of the present invention is defined by the appended claims. It is to be understood that features of the various exemplary embodiments described herein may be combined with each other, unless specifically noted otherwise. In a naive implementation, a program might be split the sorting process into three stages: (1) read unsorted data; (2) sort; (3) write sorted data. One embodiment of the system disclosed herein overlaps almost 100% of the compute time (step 2) with the time for reading (step 1) and the time for writing (step 3), reducing the total time for the second step to almost zero. Thus, the system hides the majority of the compute time for sorting by overlapping it with the time for I/O. One embodiment is directed to system that splits unsorted input data into smaller subsets as it arrives, and sorts each input subset while the subsequent input subset is being read (or received, in the case of a network file system). The system according to one embodiment performs a merge sort on the sorted subsets once the output stage begins, and performs a merge to produce an output subset while the previous output subset is being written (or transmitted, in the case of a network file system). One potential method for sorting is to use an incremental sorting mechanism like heap sort. Each time a datum arrives, it can be added to the heap. In this way, in theory at least, all data can be incrementally sorted as it arrives, and as soon as the last piece of data arrives the heap is entirely sorted and ready for output. However, it has been found that, in practice, this method is slow, because it does not exploit the locality of reference required for good performance in the CPU's memory cache. Thus, one embodiment incrementally sorts data using a quick sort, which is more FIG. 1 is a diagram illustrating a computing environment 10 suitable for implementing aspects of a system for sorting a dataset according to one embodiment. In the illustrated embodiment, the computing system or computing device 10 includes one or more processing units 12 and system memory 14. Depending on the exact configuration and type of computing device, memory 14 may be volatile (such as RAM), non-volatile (such as ROM, flash memory, etc.), or some combination of the two. Computing device 10 may also have additional features/functionality. For example, computing device 10 may also include additional storage (removable and/or non-removable) including, but not limited to, magnetic or optical disks or tape. Such additional storage is illustrated in FIG. 1 by removable storage 16 and non-removable storage 18. Computer storage media includes volatile and nonvolatile, removable and non-removable media implemented in any suitable method or technology for storage of information such as computer readable instructions, data structures, program modules or other data. Memory 14, removable storage 16 and non-removable storage 18 are all examples of computer storage media (e.g., computer-readable storage media storing computer-executable instructions that when executed by at least one processor cause the at least one processor to perform a method). Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disks (DVD) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to store the desired information and that can be accessed by computing device 10. Any such computer storage media may be part of computing device 10. The various elements of computing device 10 are communicatively coupled together via one or more communication links 15. Computing device 10 also includes one or more communication connections 24 that allow computing device 10 to communicate with other computers/applications 26. Computing device 10 may also include input device(s) 22, such as keyboard, pointing device (e.g., mouse), pen, voice input device, touch input device, etc. Computing device 10 may also include output device(s) 20, such as a display, speakers, printer, etc. FIG. 1 and the above discussion are intended to provide a brief general description of a suitable computing environment in which one or more embodiments may be implemented. It should be understood, however, that handheld, portable, and other computing devices of all kinds are contemplated for use. FIG. 1 thus illustrates an example of a suitable computing system environment 10 in which the embodiments may be implemented, although as made clear above, the computing system environment 10 is only one example of a suitable computing environment and is not intended to suggest any limitation as to the scope of use or functionality of the embodiments. Neither should the computing environment 10 be interpreted as having any dependency or requirement relating to any one or combination of components illustrated in the exemplary operating environment 10. FIG. 2 is a block diagram illustrating a system 200 for sorting a dataset according to one embodiment. System 200 includes a plurality of computing devices 204(1)-204(N) (collectively referred to as computing devices 204), and a sorting device 208, where N is an integer greater than one. In one embodiment, computing devices 204 and sorting device 208 are each implemented as computers, such as that shown in FIG. 1. Sorting device 208 is configured to sort dataset 202. In the illustrated embodiment, dataset 202 is divided into a plurality of data portions 206(1)-206(N) (collectively referred to as data portions 206), which are stored on the plurality of computing devices 204(1)-204(N), respectively. In other embodiments, dataset 202 may be stored on a single computing device. Sorting device 208 incrementally reads or receives unsorted data from data portions 206 stored on the computing devices 204. As unsorted data is being received, it is separated into independent input data subsets 210(1)-210(X) (collectively referred to as input data subsets 210) by sorting device 208, where X is an integer greater than one. As unsorted data arrives at sorting device 208, it is added to a current input data subset 210, and once the current input data subset 210 fills, it is closed, and future unsorted data that arrives goes into the next input data subset 210. Each input data subset 210 according to one embodiment has a finite capacity (e.g., 1/100 or 1/1000 of the total size of the dataset 202 to be sorted). As each subset 210 is filled, it is sorted by sorting device 208 (referred to as a "subset-sort"), thereby generating respective sorted input data subsets 211(1)-211(X) (collectively referred to as sorted input data subsets 211). In one embodiment, all of the subset-sorts, except for the last subset-sort, are overlapped with the read of the data for the subsequent subset 210. Thus, the subset-sort for each current subset is performed while the subsequent subset is being filled. In one embodiment, each of the subset-sorts is performed using a quick-sort algorithm. After the last subset 210(X) is closed, its data is subset-sorted, and then a merge-sort is performed on all of the sorted input data subsets 211 to produce a sorted dataset 212 in total sorted order. The time for performing this last subset-sort is not overlapped with I/O in one embodiment, but the amount of data in the last subset 210(X) is only a small fraction of the entire data set 202, so the subset-sort can be performed relatively quickly. The merge-sort incrementally generates (completely) sorted data from the (partially) sorted input data subsets 211. The merge-sort according to one embodiment involves repeatedly picking the smallest data element from the entire set of sorted input data subsets 211. In one embodiment, the sorted dataset 212 is divided into a plurality of sorted output data subsets 214(1)-214(Y), where Y is an integer greater than one. In one embodiment, the total number, X, of input data subsets 210 equals the total number, Y, of sorted output data subsets 214, and the input data subsets 210 have the same size (e.g., same number of data elements) as the sorted output data subsets 214. In other embodiments, the number and size of the input data subsets 210 may vary from that of the sorted output data subsets 214. In one embodiment, sorting device 208 adjusts the size of the input data subsets 210 and/or the sorted output data subsets 214 based on the size of the data set 202 (e.g., making these elements to be, for example, 1/100 or 1/1000 of the total size of the data set 202, so that these elements will be larger (i.e., contain a greater number of data elements) for a larger data set 202, and will be smaller (i.e., contain a smaller number of data elements) for a smaller data set 202. In one embodiment, the input data subsets 210 have a uniform size, and in another embodiment have a non-uniform size. In one embodiment, the sorted output data subsets 214 have a uniform size, and in another embodiment have a non-uniform size. In one embodiment, sorting device 208 is configured to dynamically size the input data subsets 210 and the sorted output data subsets 214 during the sorting process. After the first sorted output data subset 214(1) has been generated (e.g., after the first 1/100 or 1/1000 of the data in the sorted input data subsets 211 has been merge-sorted), the output or writing phase begins. In one embodiment, each subsequent portion of the merge-sort is done in the background while the results of the previous merge-sort are being output (e.g., written to disk or output to a network). Thus, sorted output data subset 214(1) is output from sorting device 208 while sorted output data subset 214(2) is being generated by sorting device 208, and sorted output data subset 214(2) is output from sorting device 208 while the next sorted output data subset 214 is being generated by sorting device 208, and this process continues until the last sorted output data subset 214(Y) is output by sorting device 208. In one embodiment, the sorted data that is being generated for each current output data subset 214 is stored in a memory cache as it is generated, and is output from the memory cache while the next output data subset 214 is being generated. In this way, by splitting the data into X shards or subsets 210, the only CPU time that is not overlapped with I/O is the time involved in subset-sorting 1/Xth of the data, followed by the time to merge-sort 1/Xth of the data. This makes virtually all of the CPU time for sorting disappear into the I/O time, even in systems where the I/O time is not much more than the compute time. For example, for subsets 210 that are each 1/100 of the total size of the input dataset 202, the only CPU time that is not overlapped with an I/O operation is the time for subset-sorting 1/100 of the total data plus the time to merge-sort 1/100 of the data. FIG. 3 is a flow diagram illustrating a method 300 of sorting a dataset according to one embodiment. In one embodiment, sorting device 208 (FIG. 2) is configured to perform method 300. At 302 in method 300, data from a dataset is incrementally received. At 304, the received data is incrementally stored as individual input data subsets as the data is received, thereby sequentially generating a plurality of filled data subsets of unsorted data. At 306, each filled data subset of unsorted data is individually sorted concurrently with receiving data for a next one of the individual input data subsets, thereby sequentially generating a plurality of sorted input data subsets. At 308, a merge sort is performed on the plurality of sorted input data subsets, thereby incrementally generating a sorted version of the dataset, wherein the sorted version of the dataset includes a plurality of sequentially generated sorted output data subsets. At 310, each of the sorted output data subsets is output concurrently with generating a next one of the sorted output data subsets. In one embodiment, the sorted output data subsets in method 300 each have a same size as the individual input data subsets. The outputting each of the sorted output data subsets in method 300 according to one embodiment comprises outputting each of the sorted output data subsets to a storage medium. In another embodiment, the outputting each of the sorted output data subsets comprises outputting each of the sorted output data subsets to a network file system. In one embodiment, a size of the individual input data subsets in method 300 is varied based on a size of the dataset. The individual input data subsets according to one embodiment each have a size that is a predetermined fraction of a size of the dataset. In one embodiment of method 300, the dataset is stored as a plurality of portions on a plurality of computing devices, and the data from the dataset is incrementally received from the plurality of computing devices. The individually sorting each filled data subset of unsorted data in method 300 according to one embodiment is performed using a quick-sort algorithm. In one embodiment, the data incrementally received from the dataset is received from a storage medium, and in another embodiment the data is received from a network file system. Although specific embodiments have been illustrated and described herein, it will be appreciated by those of ordinary skill in the art that a variety of alternate and/or equivalent implementations may be substituted for the specific embodiments shown and described without departing from the scope of the present invention. This application is intended to cover any adaptations or variations of the specific embodiments discussed herein. Therefore, it is intended that this invention be limited only by the claims and the equivalents thereof. 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A Hölder continuous function which does not belong to any Sobolev space up vote 12 down vote favorite I'm seeking a function which is Hölder continuous but does not belong to any Sobolev space. Question: More precisely, I'm searching for a function $u$ which is in $C^{0,\gamma}(\Omega)$ for $\gamma \in (0,1)$ and $\Omega$ a bounded set such that $u \notin W_{loc}^{1,p}(\Omega)$ for any $1 \ leq p \leq \infty$. Take $\Omega$ to be bounded, open. My first guess is to do a construction with a Weierstrass function. I know this is differentiable 'nowhere' but that doesn't convince me it isn't weakly differentiable in some bizarre way. Hopefully someone knows of an explicit example. ca.analysis-and-odes ap.analysis-of-pdes Function on what domain (1-dim or higher)? What exponent in your Sobolev space (L^p-flavoured or just L^2)? – Yemon Choi Sep 15 '10 at 1:07 I clarified the question. – Dorian Sep 15 '10 at 1:25 add comment 3 Answers active oldest votes Your guess is indeed right. Following a similar idea gives you the Takagi or blancmange function. It is even quasi-Lipschitz (it has a modulus of continuity $\omega(t)=ct(|\log(t)|+1)$ for a suitable constant $c>0$), thus it's Hoelder of any positive exponent less than 1. It is not even BV in any open interval, thus $W^{1,p} _ {loc}$ for no $p\geq1$. Rmk 1. The above example is for dimension 1: but of course it holds in any dimension a fortiori. Rmk 2. To get an example with a more classical flavor, actually a Weierstrass function, replace $s(x)$ with $\cos(x)$. I'd say that the resulting Fourier series defines a function with the same features, by the same reasons (the function $\cos(x)$ works better than $\sin(x),$ in view of point 2 below.) Rmk 3. Once you know that the Weierstrass function $f(x):=\sum_{k=0}^\infty 2^{-k}\cos(2^k x)$ is nowhere differentiable, you also have that it is BV on no open interval, for BV on an interval would imply differentiability a.e. there. However, for your needs it seems more direct just showing it has infinite variation on any interval. 1. To prove that the Takagi function $f(x)$ admits the above modulus of continuity, recall that that $f$ is characterized as the fixed point of the affine contraction $T:C_b(\mathbb{R})\ to C_b(\mathbb{R})$ such that $(Tf)(x)=\frac{1}{2}f(2x)+s(x),$ for all $x\in\mathbb{R}$, where $s(x)$ is the distance function from the integers (a zig-zag piecewise 1-periodic up vote 20 function). Just find a $c$ such that the subset of $C_b(\mathbb{R})$ of functions that admit $\omega$ as modulus of continuity is a $T$-invariant set. The latter subset is obviously down vote closed and non-empty, so the fixed point is there. (The above illustrated a standard general technique to prove properties of objects found by means of the contraction principle). 2. Proving that $f$ is not of bounded variation on $[0,1]$ (hence in no open interval, due to the self-similarity encoded in the fixed point equation), requires a small computation on the partial sum $f_n$ of the series defining $f$. Let $$f_n(x):=\sum_{k=0}^{n-1}\, 2^{-k} s(2^k x).$$ First note that the derivative of $f_n$ only takes integer values, which of course come as a result of the sum of $n$ terms $\pm 1$ (with all the $2^n$ possible signs). In particular, for any $n\in\mathbb{N}$ the function $f_{2n}$ has ${2n \choose n} $ flat intervals of lenght $2^{-2n}$ within the unit interval $I$, and has derivative larger than $2$ in absolute value elsewhere in $I$. Thus, for the subsequent odd index $2n+1,$ the function $f_ {2n+1}$ has ${2n \choose n}$ local maxima in $I$ (located in the mid-points of the above intervals). Moreover, passing to $f_{2n+1}$ each maximum point contributes to the increment of the total variation with $2^{-2n}$, while the total variation remains unchanged passing from $2n+1$ to the next even index $2n+2$. The conclusion is that, for any $n$, the total variation of $f_n$ on $I$ is $$V(f_n;I)=\sum_{0\leq k < n/2}{2k\choose k}2^{-2k} =O\big(\sqrt{n}\big),$$ since by the classical asymptotics for the central binomial coefficient, ${2k \choose k}=\frac{4^k}{\sqrt{\pi k}}(1+o(1)),\, k\to\infty.$ So actually $V(f_n;I)$ diverges. Yet this would not be sufficient to conclude that $V(f,I)=\infty,$ as the total variation is only lower semicontinuous with respect to the uniform convergence. However, the discrete variation on a given subdivision $P:=\{t_0 < \dots < t_r \}$ $$V(f_n; P\, )=\sum_{i=0}^{r-1}\, \big|f_n(t_{i+1})-f(t_i)\big|$$ does of course pass to the limit under even pointwise convergence. Now the point is that, for the binary subdivision $P_m:=\{ k2^{-m} \, : \, 0 \le k \le 2^m \},$ we have $V(f_n;I)=V(f_n;P_m)$ as soon as $n \geq m$. So for all $m$ letting $n\to\infty$ $$V(f;P_m)=\lim_{n\to\infty }V(f_n;P_m)=V(f_m;P_m)$$ and $$V(f;I)=\sup_{m\in\mathbb{N}}V(f;P_m)=\infty,$$ as we wished to show. add comment Another simple approach is to take the lacunary series $f(x)=\sum_k a_k e^{i(m_k,x)}$ where $m_k\in \mathbb Z^d$ and $|m_{k+1}\gg |m_k|$. For any modulus of continuity $\omega$ such that $\ Omega(t)=\omega(t)/t\to \infty$ as $t\to 0$, the condition that $f$ has this modulus of continuity is equivalent to the condition that $|a_k|\le C\omega(|m_k|^{-1})$ if the spectrum is sparce enough to ensure that $\Omega(|m_{k+1}|^{-1})\ge 2\Omega(|m_k|^{-1})$ and $\omega(|m_k|^{-1})\ge\sum_{\ell>k}\omega(|m_\ell|^{-1})$. If $f\in W^{1.p}$, then $ \left|\int f\nabla\psi\ right|\le C\|\psi\|_{L^q}$ for smooth $\psi$. Plugging $e^{-i(m_k,x)}$, we see that unless $a_k=O(|m_k|^{-1})$, we have no chance. Thus, nothing short of Lipschitzness will force $f$ to be up vote in $f\in W^{1.p}$. 6 down vote This formally works only on the torus but you can take any smooth partition of unity $g_j$ on the torus and notice that one of the functions $g_j f$ is also bad. But any of them can be replanted to $\mathbb R^d$ if the supports are small enough. Nice argument... so if I got it this way you can make a counterexample with any modulus of continuity satisfying $t=o(\omega(t).$ – Pietro Majer Sep 15 '10 at 13:34 1 A doubt. If we choose $a_k:=2^{-k}$ and $m_k:=\pi2^k$ the resulting $f$ is a Weierstrass function (or better its real part); which in this case is nowhere differentiable (with these parameters I think its a result by Hardy), hence certainly not locally lipschitz. But the condition you wrote holds with $\omega(t)=t$. – Pietro Majer Sep 15 '10 at 14:39 You are right, I was a little bit sloppy in how exactly I stated it. I'll ix it now. – fedja Sep 15 '10 at 14:46 add comment I believe that the Cantor ternary function (aka devil's staircase) is a simple example. up vote 1 down vote For Holder exponent $< \log_3 2$. – Willie Wong Dec 8 '10 at 0:23 add comment Not the answer you're looking for? Browse other questions tagged ca.analysis-and-odes ap.analysis-of-pdes or ask your own question.
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Estimating the reproductive number in the presence of spatial heterogeneity of transmission patterns Estimates of parameters for disease transmission in large-scale infectious disease outbreaks are often obtained to represent large groups of people, providing an average over a potentially very diverse area. For control measures to be more effective, a measure of the heterogeneity of the parameters is desirable. We propose a novel extension of a network-based approach to estimating the reproductive number. With this we can incorporate spatial and/or demographic information through a similarity matrix. We apply this to the 2009 Influenza pandemic in South Africa to understand the spatial variability across provinces. We explore the use of five similarity matrices to illustrate their impact on the subsequent epidemic parameter estimates. When treating South Africa as a single entity with homogeneous transmission characteristics across the country, the basic reproductive number, R[0], (and imputation range) is 1.33 (1.31, 1.36). When fitting a new model for each province with no inter-province connections this estimate varies little (1.23-1.37). Using the proposed method with any of the four similarity measures yields an overall R[0] that varies little across the four new models (1.33 to 1.34). However, when allowed to vary across provinces, the estimated R[0] is greater than one consistently in only two of the nine provinces, the most densely populated provinces of Gauteng and Western Cape. Our results suggest that the spatial heterogeneity of influenza transmission was compelling in South Africa during the 2009 pandemic. This variability makes a qualitative difference in our understanding of the epidemic. While the cause of this fluctuation might be partially due to reporting differences, there is substantial evidence to warrant further investigation. Influenza; Reproductive number; Infectious disease outbreak In an emerging outbreak of an infectious disease, such as influenza, there is great interest in determining, amongst other things, its transmissibility, which is typically quantified by its reproductive number. Initially, there is interest in estimation of the idealized basic reproductive number, R[0], which measures the average number of cases generated by an infected individual in an entirely susceptible population. Post hoc analyses of an outbreak may include estimation of the time-varying effective reproductive number, R[t], which represents the impact on R[0] of acquired immunity and public health interventions that typically lead to decreased transmission and a decrease in the growth of the outbreak [1]. Several methods exist for estimating these quantities either in real time as the epidemic progresses, or after the epidemic is over [2,3]. Frequently, these estimators assume a homogenously mixing population, even though often this simplifying assumption may not be realistic. One possible source of heterogeneity is the lack of spatial uniformity in transmission across the population in question. In such an instance, the question arises of how to modify our inference—on the reproductive number, for example—and the impact this might have on our understanding of transmission dynamics. Typically epidemiological studies of influenza report reproductive numbers over large geographic regions and populations, often estimating a reproductive number for an entire country [4,5]. This may be useful as a metric to compare to previous measures of the same quantity in an effort to determine relative transmissibility of a disease. However, this overall measure confounds information that may impact on transmissibility, or its measure, and it is likely not an insufficiently informative representation of the reproductive number. Many studies have attempted to measure the spatial dynamics of influenza spread, often in an effort to create better control strategies and predict the occurrence of specific strains in coming influenza seasons [6-8]. Implicit in this work is the reality that influenza transmission dynamics are not spatially uniform, though details of how transmission may vary spatially are lacking. Spatial considerations are clearly important, as those who live great distances from each other are much less likely to infect one another than those who live in closer proximity to each other. Further, spatial heterogeneity is important to consider since differences may exist in behavioral patterns, demographics, control measures, climate, and other factors that may affect transmission differently in different geographical regions. The issue is made even more complex because reporting issues and healthcare seeking behaviors can vary geographically and also influence data quality. Thus identifying heterogeneity does not necessarily indicate its cause simply. In this work we introduce a simple modification of the method originally proposed by Wallinga and Teunis [1] to estimate the effective reproductive number. This modification allows for the estimation of the reproductive number(s) in the presence of greater heterogeneity in transmission. We apply this method to data from the 2009 pandemic influenza outbreak in South Africa and estimate the reproductive number for each province. We discuss the potential implications of the results we obtain on future research and surveillance activities. Wallinga and Teunis [1] (denoted WT method hereafter) proposed a network-based method for the estimation of the effective reproductive number by making use of the epidemic curve, N={N[1],…, N[T]}, where N[t] is the number of cases at time point t, and an estimate of the serial interval, p[1],…, p[k], where p[i] describes the probability of a serial interval of length i and the maximum serial interval length is k. The estimator for R[t] is a function of the relative probability that case t[i] was infected by the j^th case on day t′, denoted q t i , t ′ j and is given by R t j ' = ∑ s = t ′ + 1 min T , t ′ + k ∑ i = 1 n s q s i , t j ' = ∑ s = t ′ + 1 min T , t ′ + k n s q s , t j ' , where n[s] denotes the number with symptom onset on day s. The relative probability that case t[i] was infected by the j^th case on day t ′ , q t i , t ′ j , is a function of the probability that case t[i] was infected by case t[j]′, and is entirely a function of the serial interval, such that P(t[j]′ →t[i]) = p t i − t ′ j . Spatial transmission data We propose the use of additional structure to describe the probability of an infection event occurring between two cases. We modify the probability of an infectious event between two cases, P(t[j]′ →t[i]), to incorporate spatial information: P t ′ j → t i = p t i − t ′ j d t i ′ t j , where d[ti′ ,tj] is a measure of similarity between the cases t[j]′ and t[i]. Note we assume independence between space and the serial interval. By making use of information on conditional probabilities, if known, one could relax this assumption. Since this method only modifies the method of constructing the probabilities that connect individuals in the network, the properties of the estimator originally proposed by Wallinga and Teunis still apply. This measure can be calculated in a number of ways. The simplest being d t i ′ t j = 0 , if the cases are far apart , 1 , if the cases are close to each other . The similarity measure can depend on geographical proximity and/or demographic proximity, and can also be informed by observed data on travel or contact patterns. The similarity matrix does not necessarily contain probabilities, but represents the relative similarity between two locations and/or demographic features. Additionally by similarity we are describing the potential for an infective event. Alternatively, we can also entertain a Bayesian formulation and attach a prior to the parameters of the distance measure. Below, we investigate some different measures. We use data from South Africa describing the pandemic influenza H1N1 outbreak in 2009. The data contains information on 12,543 reported laboratory confirmed cases, including specimen collection date, gender, age, province of residence, and symptom onset date [9]. There are nine provinces in South Africa that vary substantially in size, population density, climate, and accessibility to healthcare [10]. The symptom onset date was available in 758 cases (6% of the cases). We impute the missing onset dates using a multiple imputation method. To this end we first fit a Poisson model to the lag between onset date and collection date for those who had both dates recorded (715 cases) incorporating statistically significant predictors: (i) the province where the report originated, and (ii) an indicator of weekend versus weekday for the day of collection. The Poisson model was used to randomly generate missing onset times. This process was repeated 500 times creating 500 imputed data sets. All analyses are performed on each of the 500 imputed datasets and results are combined across the individual dataset results and these summaries are the ones we report [11]. Our model requires a similarity matrix. As we are uncertain of which similarity matrix would be most appropriate for influenza in South Africa in 2009, we investigate a variety of matrices in the model and comment on the variability resulting from each similarity matrix. To this end, we investigate five different similarity matrices to describe, what would seem to us to be, plausible transmission patterns between the provinces. The matrices are shown in Tables 1, 2, 3, 4, 5 and are, respectively: Table 1. All transmission occurs within provinces Table 2. Matrix based on reported travel patterns in South Africa Table 3. Uniform probability of transmission between different provinces Table 4. Increased probability of transmission for neighboring provinces Table 5. Increased transmission for most densely populated provinces a. Diagonal matrix. This model assumes that all transmissions occur within each province and there is no transmission between individuals in different provinces. This is comparable to applying the original WT method to each province separately. b. Travel patterns. Using data on travel patterns reported by the Department of Environmental Affairs and Tourism in South Africa [12] we construct a second transmission matrix. This one assumes that transmission probabilities mirror the probability of travel between provinces. c. Increased transmission between those in the same province, i.e. d[ij]=2 if i and j are in the same province and d[ij]=1 otherwise. This is an attempt at giving more weight to infection between individuals within a state, but allowing for infection from an individual from another state; a less extreme isolation model than in a., above. Of course, we could entertain values other than 1 and 2 for elements of this matrix. d. Neighboring provinces up-weighted. We define a similarity metric such that if i and j are in the same province the similarity is 2, if they are in neighboring provinces the similarity is 1, otherwise the similarity is 0.5. This model can be thought of as between the model described in a. and the one described in c. e. Higher transmission between densely populated provinces. This matrix allows the three provinces that are the most populous and likely experience the greatest rates of travel to have a greater chance of cross infection. This is done by using the same arrangement as described in c., but allowing the provinces of Gauteng, West Cape, and KwaZulu-Natal to have a similarity measure of 1.5 to each other. This approach requires an estimate of the serial interval. We make use of the SI distribution between primary cases and suspected plus laboratory-confirmed secondary cases (30%, 17%, 20%, 23%, 7% and 3% for days 1 to 6, respectively) [11]. Sensitivity analysis We also perform a sensitivity analysis to assess the robustness of our results to potential errors in the data. Our general approach is to allow the onset date of 10% of the individuals to shift randomly within a 30-day window. We choose one imputed dataset and create fifty “sensitivity” data sets. All analyses are performed on these 50 datasets and compared to the results for the imputed dataset used in the original analysis. Complete results are reported in the appendix. All analyses were performed in R 2.13.0 (http://www.r-project.org webcite). Programs are available upon request to the corresponding author. Figures 1 and 2 show a sample of the imputed epidemic curves first overall (Figure 1) and then for each of the nine provinces (Figure 2). The first case had symptom onset on June 12, 2009 and the final specimen was collected on November 23, 2009. Gauteng Province had the largest number of cases with 5541 confirmed cases during the epidemic. Figure 1. Imputed epidemic curves. Gray shading indicates the variability in the imputed data. The dashed line indicates the observed onset data. Figure 2. Epidemic curves for each of the nine provinces. The shaded area indicates the variability in the imputed values. Figure 3 shows the overall estimates of R[t] when the different transmission matrices are used, as well as when the original WT method (Matrix a, ignoring spatial transmission patterns) is used. We note that there are only very minor differences between the estimates. The only noticeable differences exist during the initial and final phases of the epidemic; however, these differences are minimal. Figure 4 shows the results by province, and again there are only minor differences between the estimates obtained with the five different transmission matrices. Figure 3. Estimates of R[t ]using the transmission matrices, as described in the text. The estimates shown represent the average of the R[t] estimates obtained across the 500 imputed epidemics. Days when no cases were reported have a R[t] of 0, though we smooth through this for the purpose of visual presentation. Figure 4. Estimated R[t ]by province. The line types for each plot are the same as those used in the previous figure. Days when no cases were reported have a R[t] of 0, though we smooth through this for the purpose of visual presentation. Table 6 shows an estimate of R[0] obtained by averaging the R[t] estimates obtained over the period of exponential growth in the epidemic (days 10 through 70 reported, though other ranges were used with similar results). We note sizable differences in the estimate of R[0] between provinces and the transmission matrices used. The biggest differences are between the original WT method (Matrix a) and the methods using a nonhomogeneous transmission matrix (Matrix b-e). Those using a similarity matrix implying heterogeneity are almost identical to each other, but quite different from the value obtained by the original WT method that assumes homogeneity. We note that when nonhomogeneous transmission is assumed, R[0] is only above 1 for Gauteng and the Western Cape, where Johannesburg and Cape Town are located. One possible explanation is that a certain population density or degree of travel in/out of an area is required to sustain a local epidemic of the flu. The sensitivity analysis yielded results that are consistent with these findings (Table 1). Table 6. The R[0 ]estimates overall and by region We further explore this result in Figure 5, where the estimates of R[0] are plotted against the population size, land area and population density with the least squares regression estimates shown. The estimate of R[0] increases with an increase in population size and density (p=0.0004 for matrix b; p=0.04 for matrix c) and decreases with land area. The proportion infected in each province also appears to be related to the population size in the province, though this is not significant (p=0.16). When the WT estimator is used, the model that ignores geography, these relationships disappear (p=0.53 for population density; similar results hold for the other plots), as one might expect. Figure 5. The relationship between characteristics of each of the provinces and the outbreak. Lines drawn reflect the least squares regression line for the relationship between the two variables. The first panel shows the relationship between the population size and the size of the outbreak in each province. The second panel describes the relationship between the population size and R[0]. The third panel illustrates the relationship between the land area and R[0] obtained for each of the transmission matrices. The final panel plots the relationship between population density and R[0] for each transmission matrix. Line types follow the legend in Figure 3. The results in this paper argue that disease transmission is a function of more than just biology, as is well known, but often ignored. The impact of adjusting the assumption of homogeneous mixing in this South African outbreak, is that apart from the densely populated, urban areas, the pandemic would likely not have been sustained just in the rural, sparsely populated provinces. This finding reinforces the obvious: if individuals have very limited contact with each other, then the outbreaks would probably be small in numbers, limited to small groups, and would likely not propagate to become a larger and more noticeable outbreak. Our estimates of the reproductive number for the more populous provinces are consistent with results reported elsewhere, but the results we obtain for more rural provinces are notably lower [5,13,14]. In our analysis, there are other important issues to consider. Throughout we have assumed that the reporting of cases is uniform throughout the country, and this was the basis for our sizable imputation of the number of symptom onset dates. Even if this reporting is less than 100%, but still spatially uniform, the results we observe will hold [15]. However, if reporting is not uniform between provinces and some provinces have much better reporting of cases than others, we can expect the results to change. For instance, if reporting was lower in the more rural provinces, then it is likely that the estimated reproductive numbers would increase in these provinces if some adjustment for this underreporting were made. Without a more detailed study, this is difficult to quantify and explain. Clearly, there is a certain amount of confounding present, and data reporting issues can be part of an explanation for the results we obtain. Another factor that can, at least partly, explain the results are the choice of transmission matrices used. We show results for various transmission matrices in order to quantify the degree to which transmission occurs between provinces. Four of these matrices are somewhat arbitrary and not based on actual data. One matrix is based on actual travel patterns in South Africa. But the results are reasonably consistent for the four matrices that assume some degree of transmission between provinces, even when the amount is very small, as in the travel-based matrix. This argues that the results are influenced more by the fact that such a matrix is used and less by the form that such a matrix takes. In all of these cases, despite the substantial differences in the matrices, the result is the same: transmission is maintained in more urban areas and rural areas fail to sustain transmission. We note dramatic differences between the results when transmission between provinces is incorporated into the estimation (matrices b-e) and the results that assume that no transmission occurs between provinces (matrix a). This reflects the impact of using such matrices and the importance of performing sensitivity analyses to determine the impact of the matrix on the results. Possibly why such matrices have not been used in the past, even though they have a qualitative impact on the results, is that these matrices are difficult to come by, and in practice, they are likely to be estimated in a somewhat ad hoc manner. In some cases, there may be little or no data to inform a transmission matrix. In this case, a wide variety of matrices can be used to determine the plausible range of values that the estimates can assume. Ultimately deriving a method for estimating these matrices, ideally using Bayesian tools, would mitigate this challenge. The framework we provide here lends itself to such an approach, although we have not carried out such an analysis. We further note the coarseness of the spatial resolution of our data. Our implicit assumption is that individuals within a province are homogenous. While assuming homogeneity within a province is more general than assuming homogeneity over the entire country, it is still a substantial assumption that ignores potentially important variations within a province. As with any analysis, we are limited by the available data, and acknowledge that data on a finer spatial scale would be desirable. Our method also makes a strong assumption of independence between space and time. That is, we assume that the probability of a particular infector-infectee pair is influenced independently by the temporal and spatial distance between the two individuals. Clearly violations of this assumption are feasible and could impact our results. Without further information on the potential correlations that exist between space and time, any adjustment would be arbitrary and potentially misleading. While the results we obtain might partially be explained by data quality issues and care-seeking behaviors in rural versus urban populations, there are other potential explanations. A recent cross sectional, serum study reports differential exposure to influenza strains in China across five communities [16], with the most urban community reporting the highest exposure to influenza strains. This provocative result begs further study as it is likely to be attributable to a number of factors and is consistent with the results we have obtained here. The marked difference in estimates of transmission in rural versus urban areas in our study is also consistent with recent work on social contacts [17,18]. In a study in Japan, there was a significant relationship between the number of social contacts and urbanicity amongst the elderly. Additionally, they similarly found that those in more urban areas have a greater chance of having more supportive interactions [17]. Influenza transmission requires proximity between individuals and social contacts could be one surrogate measure of this proximity. Additionally, there has been an observed influence of climate and relative humidity on influenza transmission [19-22]. The climate across South Africa is variable with some of the more rural provinces being characterized by a drier climate; the country’s climate is mostly semi-arid, but subtropical along the east coast. So this is not an ideal country to test the transmission theory, but KwaZulu-Natal is the only relatively humid province, so it does not appear that the humidity hypothesis is borne out by these data. Travel patterns have been correlated with the movement of influenza on a large scale [6,7]. Indeed, Viboud et al show that an outbreak that starts in a rural area will spread slowly until it reaches an urban center, at which point it will spread much more quickly [6]. We attempt to incorporate travel patterns in South Africa in our analysis. Travel between the more rural provinces and other areas is much more limited and in general individuals tend to travel to larger provinces, rather than individuals in more urban provinces coming to rural provinces. Thus, the lack of movement between these provinces and areas where transmission is occurring could lead to later onset of sustained transmission locally and lower levels of transmission in the absence of more individuals entering the province and interacting with the local population. Another explanation is that what we see here could be similar to that observed in the Netherlands in the early phases of the pandemic where the reproductive number was estimated to be below one, indicating that sustained transmission was not occurring and the cases were being generated through imported infections [4]. In South Africa, this would imply that individuals traveled to larger urban centers and became infected there. Their case was reported upon returning home so that the case is not attributed to the location where the transmission event actually took place, at least for the initial cases. We did not account for the possibility of this taking place. There has been significant work pointing to the great spatial heterogeneity that exists in influenza; however little work has been done to directly estimate the influence of local transmission in propagating this trend. Intensive network models have the capability of investigating these dynamics, but are challenging to implement without extensive resources. Our study introduces a novel and simple approach for doing this by making use of the epidemic curve, information on the serial interval distribution and some prior knowledge of transmission dynamics. We have shown results for estimation over the entire outbreak period, but the modification proposed by Cauchemez et al [2] allowing for real-time estimation of R[t] could be implemented straightforwardly with this modification, as well. Our results are suggestive of substantial spatial heterogeneity in transmission dynamics, however further study is warranted due to the limitations of the data at hand and uncertainties on reporting dynamics. At a minimum, these results should argue for modifications in the data that is collected from surveillance and other data collection systems to better understand reporting patterns and the dynamics of interaction between individuals that would lead to substantial heterogeneity in transmission. An improved understanding of heterogeneity will aid in targeting limited interventions in the most effective way possible. Authors’ contributions LFW and MP conceived the study and developed the methods used. LFW performed the analyses and wrote the manuscript. BA collected the data. All authors reviewed the manuscript. All authors read and approved the final manuscript. LFW and MP were supported by Award Number U54GM088558 from the National Institute of General Medical Sciences. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute Of General Medical Sciences or the National Institutes of Health. Sign up to receive new article alerts from International Journal of Health Geographics
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Efficient Light-Scattering Calculations for Aggregates of Large Spheres Calculation of the scattering pattern from aggregates of spheres through the T-matrix approach yields high-precision results but at a high-computational cost, especially when the aggregate concerned is large or is composed of large-size spheres. With reference to a specific but representative aggregate, we discuss how and to what extent the computational effort can be reduced but still preserve the qualitative features of the signature of the aggregate concerned. © 2003 Optical Society of America OCIS Codes (190.5890) Nonlinear optics : Scattering, stimulated (290.1990) Scattering : Diffusion (290.4210) Scattering : Multiple scattering (290.5850) Scattering : Scattering, particles Rosalba Saija, Maria Antonia Iatì, Paolo Denti, Ferdinando Borghese, Arianna Giusto, and Orazio I. Sindoni, "Efficient Light-Scattering Calculations for Aggregates of Large Spheres," Appl. Opt. 42, 2785-2793 (2003) Sort: Year | Journal | Reset 1. H. C. van de Hulst, Light Scattering by Small Particles (Wiley, New York, 1957). 2. P. J. Wyatt, “Scattering of electromagnetic plane waves from inhomogeneous spherically symmetric objects,” Phys. Rev. B 127, 1837–1843 (1962). 3. M. I. Mishchenko, W. J. Wiscombe, J. H. Hovenier, and L. D. Travis, “Overview of scattering by nonspherical particles,” in Light Scattering by Nonspherical Particles, M. I. Mishchenko, J. W. Hovenier, and L. D. Travis, eds. (Academic, New York, 2000), pp. 30–59. 4. S. Holler, J.-C. Auger, B. Stout, Y. Pan, J. R. Bottiger, R. K. Chang, and G. Videen, “Observations and calculations of light scattering from clusters of spheres,” Appl. Opt. 39, 6873–6887 5. M. I. Mishchenko, J. W. Hovenier, and L. D. Travis, “Concepts, terms, notation,” in Light Scattering by Nonspherical Particles, M. I. Mishchenko, J. W. Hovenier, and L. D. Travis, eds. (Academic, New York, 2000), pp. 3–25. 6. J. D. Jackson, Classical Electrodynamics (Wiley, New York, 1975). 7. F. Borghese, P. Denti, R. Saija, G. Toscano, and O. I. Sindoni, “Multiple electromagnetic scattering from a cluster of spheres. I. Theory,” Aerosol Sci. Technol. 3, 227–235 (1984). 8. F. Borghese, P. Denti, G. Toscano, and O. I. Sindoni, “An addition theorem for vector Helmholtz harmonics,” J. Math. Phys. 21, 2754–2755 (1980). 9. F. Borghese, P. Denti, and R. Saija, “Optical properties of spheres containing several spherical inclusions,” Appl. Opt. 33, 484–491 (1994). 10. P. C. Waterman, “Symmetry, unitarity and geometry in electromagnetic scattering,” Phys. Rev. D 3, 825–839 (1971). 11. E. Fucile, F. Borghese, P. Denti, R. Saija, and O. I. Sindoni, “General reflection rule for electromagnetic multipole fields on a plane interface,” IEEE Trans. Antennas Propag. 45, 868–875 12. E. Fucile, P. Denti, F. Borghese, R. Saija, and O. I. Sindoni, “Optical properties of a sphere in the vicinity of a plane surface,” J. Opt. Soc. Am. A 14, 1505–1514 (1997). 13. Y.-L. Xu, “Electromagnetic scattering by an aggregate of spheres: far field,” Appl. Opt. 36, 9496–9508 (1997). 14. F. Borghese, P. Denti, R. Saija, and O. I. Sindoni, “Reliability of the theoretical description of electromagnetic scattering from non-spherical particles,” J. Aerosol Sci. 20, 1079–1081 (1989). 15. R. T. Wang, J. M. Greenberg, and D. W. Schuerman, “Experimental results of dependent light scattering by two spheres,” Opt. Lett. 11, 543–545 (1981). 16. D. W. Schuerman and R. T. Wang, “Experimental results of multiple scattering,” Contractor Rep. ARCSL-CR-81003 (U.S. Army Chemical Systems Laboratory, Aberdeen Proving Grounds, Md., July 1980). 17. B. Stout, J.-C. Auger, and J. Lafait, “Individual and aggregate scattering matrices and cross sections: conservation laws and reciprocity,” J. Mod. Opt. 48, 2105–2128 (2001). 18. D. W. Mackowski and M. I. Mishchenko, “Calculation of the T matrix and the scattering matrix for ensembles of spheres,” J. Opt. Soc. Am. A 13, 2266–2278 (1996). 19. M. I. Mishchenko, L. D. Travis, and A. Macke, “T-Matrix method and its applications,” in Light Scattering by Nonspherical Particles, M. I. Mishchenko, J. W. Hovenier, and L. D. Travis, eds. (Academic, New York, 2000), pp. 147–172. 20. F. Borghese, P. Denti, R. Saija, M. A. Iatì, and O. I. Sindoni, “Optical properties of a dispersion of anisotropic particles with nonrandomly distributed orientations. The case of atmospheric ice crystals,” J. Quant. Spectrosc. Radiat. Transfer 70, 237–251 (2001). 21. W. C. Chew, Waves and Fields in Inhomogeneous Media, IEEE Press Series on Electromagnetic Waves (Institute of Electrical and Electronic Engineers, Piscataway, N.J., 1990). 22. M. I. Mishchenko and D. W. Mackowski, “Electromagnetic scattering by randomly oriented bispheres: comparison of theory and experiment and benchmark calculations,” J. Quant. Spectrosc. Radiat. Transfer 55, 683–694 (1996). 23. J. R. Bottiger, E. S. Fry, and R. C. Tompson, “Phase matrix measurements for electromagnetic scattering by sphere aggregates,” in Light Scattering by Irregularly Shaped Particles, D. W. Schuerman, ed. (Plenum, New York, 1980), pp. 283–290. OSA is able to provide readers links to articles that cite this paper by participating in CrossRef's Cited-By Linking service. CrossRef includes content from more than 3000 publishers and societies. In addition to listing OSA journal articles that cite this paper, citing articles from other participating publishers will also be listed. « Previous Article | Next Article »
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Brooklawn, NJ Precalculus Tutor Find a Brooklawn, NJ Precalculus Tutor ...I have a proven track record of increasing students' ACT and SAT scores and improving their skills. My approach is tailored specifically to the student, so no two programs are alike. My expertise allows me to quickly identify students' problem areas and most effectively address these in the shortest amount of time possible. 19 Subjects: including precalculus, calculus, statistics, geometry ...There is someone uniquely delightful about seeing someone "get" subject matter that they did not get before, and knowing that you were a part of that. Besides working at college, I have worked as a teacher, co-teacher, and student aide in middle and high schools. I enjoy working with teens, and I generally get along pretty well with them. 16 Subjects: including precalculus, English, calculus, physics ...While I have mostly taught all levels of calculus and statistics, I can also teach college algebra and pre-calculus as well as contemporary math. My background is in engineering and business, so I use an applied math approach to teaching. I find knowing why the math is important goes a long way towards helping students retain information. 13 Subjects: including precalculus, calculus, algebra 1, geometry ...I am not there to do your homework, I'm there to help you through the concepts so you can do the homework yourself. After all, I won't be there when you take the test! See you at our first 14 Subjects: including precalculus, chemistry, algebra 1, algebra 2 ...My goal is to help my students become lifelong writers (and readers), not only to master a test. Areas of instruction include: SAT Writing SAT Critical Reading SAT Math GRE Verbal GRE Quantitative Reasoning GRE Analytical Writing MCAT verbal GMAT Praxis I Praxis English Subject Area TEAS Readi... 47 Subjects: including precalculus, chemistry, reading, writing Related Brooklawn, NJ Tutors Brooklawn, NJ Accounting Tutors Brooklawn, NJ ACT Tutors Brooklawn, NJ Algebra Tutors Brooklawn, NJ Algebra 2 Tutors Brooklawn, NJ Calculus Tutors Brooklawn, NJ Geometry Tutors Brooklawn, NJ Math Tutors Brooklawn, NJ Prealgebra Tutors Brooklawn, NJ Precalculus Tutors Brooklawn, NJ SAT Tutors Brooklawn, NJ SAT Math Tutors Brooklawn, NJ Science Tutors Brooklawn, NJ Statistics Tutors Brooklawn, NJ Trigonometry Tutors
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Copyright © University of Cambridge. All rights reserved. 'Right Angles' printed from http://nrich.maths.org/ Samantha and Shummus both realised that in order to create a triangle with a right angle, the band had to go through the centre of the circle. Shummus writes: I noticed that the bands had to be started in the centre. Xianglong Ni notes that: If we have 9 points on the circle then you can't create a right-angle using the points. This is so because a right angle is inscribed in a semicircle; It is facing a diameter. But you can only create a diameter when there is an even amount of points on the circle. If the number of points on the circle is even then yes. If the number is odd then no. Rachel from Newstead sent us a few diagrams to illustrate examples of right-angled triangles in circles with an even number of points. Indika of Helena Romanes 6th Form College sent us her explanation for why the band must go through the centre of the circle: The only way that a right angle triangle can be created between 3 points round the edge is when the angle subtended at the centre by two of the points is 180 degrees, this therefore proves that two of the points have to be opposite each other (this means having an equal number of pegs). This is because the angle subtended at the centre by two points are exactly double the angle subtended at the edge by the same points. This rule will apply to all circles, i.e. there will be a right angled triangle if two pegs are placed opposite each other. If you haven't met this idea before, you may want to look at another problem from August 2005, Subtended angles Here are another couple of examples of right-angled triangles using the same eight-point and ten-point circles that Rachel used:
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second order variable coeff homogeneous ode May 6th 2010, 01:31 PM #1 May 2010 second order variable coeff homogeneous ode Could someone help me solve the following: y'' +(1/3x)y' - (1/3x)y = 0 I go through the steps I would normally to solve the DE, but when attempting to find the roots I end up with a function of x which I'm not exactly sure what to do with. It appears that there must be different solutions for different ranges of x. How would I go about solving this? Could someone help me solve the following: y'' +(1/3x)y' - (1/3x)y = 0 I go through the steps I would normally to solve the DE, but when attempting to find the roots I end up with a function of x which I'm not exactly sure what to do with. It appears that there must be different solutions for different ranges of x. How would I go about solving this? Are you sure the ODE is $<br /> y'' + \frac{1}{3x} \, y' - \frac{1}{3x} \, y= 0?<br />$ yes, confusing... isn't it? just so everyone knows, I'm pretty sure this is solved using the Frobenius method You are correct, we just need to switch our variables around to obtain the required equation for the Frobenius method: Frobenius method - Wikipedia, the free encyclopedia $<br /> x^2 y'' + \frac{1}{3} xy' - \frac{1}{3} x y= 0<br />$ $p(x) = \frac{1}{3}$ $q(x) = \frac{1}{3} x$ Then continue with the Frobenius method. There is an excellent example on that wikipedia page (first example) that will walk you through all the steps (so I won't repeat them here out of May 6th 2010, 01:47 PM #2 May 6th 2010, 02:05 PM #3 May 2010 May 6th 2010, 05:04 PM #4 May 2010 May 7th 2010, 08:26 AM #5
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Div, Grad, Curl and All That Cosmic Variance had three interesting &ldquot;greatest&rdquot; discussion threads: In the comments to the Greatest Physics Textbook, Clifford (the original poster) joked that no self-respecting mathematician ever read Schey’s Div, Grad, Curl and All That. I don’t know about anyone else, but that’s the book I learned the subject from. The book gives incredibly hand-wavy proofs, and if I remember right it trumpets its lack of rigor, but it does a good job of giving the intuition behind the Green, Gauss, and Stokes theorems. Reading it made reading something like Spivak’s Calculus on Manifolds much easier. 7 thoughts on “Div, Grad, Curl and All That” 1. Is it just me, or was the first time you saw this stuff slightly mystifying, but when you see the material in the Manifolds context, the results seem almost obvious? (I mean aside from the being new to the material vs not being new to the material) 2. Actually, I think I was the opposite. I tried to learn it from the manifolds point of view, and didn’t get any feel for what it was about. What finally allowed to learn it was hearing the sentence “the determinant of a matrix is a volume”, hearing the sentence “the derivative of volume is surface area”, and then reading Div, Grad, Curl and All That which explains all of the vector calculus theorems from the “derivative of volume is surface area” point of view. Then I was able to make sense of it from the manifolds point of view. (Unless by “manifolds point of view”, you just mean that differential forms are much easier to understand than curl. Then I agree. In fact, I’ve completely forgotten everything I’ve ever known about curl.” 3. I guess I mean the latter. I too have forgotten everything I ever knew about curl except for how to spell it. 4. For good intuition about calculus on manifolds I recommend Misner, Thorne and Wheeler’s ‘Gravitation’ which has nice pictures of forms. When I think about differential forms I actually use a ‘dual’ form of MWT’s diagrams that I’ve described (very handwavingly) here. 5. My link vanished. ‘here’ should point to: http://homepage.mac.com/sigfpe/Mathematics/forms.pdf
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Introducing myself My name is David Corfield and I'm very grateful to have been invited to join this blog as a contributor. With five years of blogging behind me at the -Category Café, I relish the opportunity to talk with a new audience. My rate of blogging may have slowed, especially as my adminstrative load has increased - I'm now Head of at the University of Kent - but I'm looking forward to writing some posts here. I have interests in a variety of approaches to mathematical philosophy, including the statistical learning theory I picked up from my time at the Max Planck Institute for Biological Cybernetics in Tübingen, but the main idea I would like to promote to the audience here is that category theory is worth exploring as a resource for the mathematical philosopher. I have recently published a couple of articles which examines the light category theory can throw on familiar infinite structures. In Understanding the Infinite I: Niceness, Robustness, and Realism , I look at the phenomenon where an infinite entity is defined by a universal property, and through this inherits 'for free' a range of other nice properties. In Understanding the Infinite II: Coalgebra , I look at the duality between minimally and maximally defined entities in the context of the duality between 'algebra' and 'coalgebra'. Perhaps had I known of Shaughan Lavine (1994) Understanding the Infinite , Harvard University Press, I might have opted for a different title. There's much to do to understand the relationship between category theory and the traditional foundational branches, which have drawn most philosophical attention. Recently, I posed a on MathOverflow concerning category theory and Joel Hamkins' set theoretic multiverse. The answer by Joel there shows just the sort of joint investigation needed. A few years ago at the Café, we had on the relationship between category theory and model theory. Category theory also has an interface with proof theory , but I know less about this. Something to look out for in the future is the new Homotopy type theory , and associated Univalent foundations 8 comments: 1. Cool! Glad to have you as a contributor, David - Jeff 2. Welcome, David! So this is at least one fruitful outcome of our meeting in Gent last month :) (Hopefully, there will be others...) I look forward to your M-Phi posts! 3. Could this post be tagged "PlanetMO" so that it can be found at mathblogging.org/planetmo ? 4. The views of my MO question have risen to 997, only 3 more for a badge. Sad how enjoyable these pointless rewards are. Peter, I'm not sure what you're asking for. 5. David, I think on blogspot tags are called "labels", they can be added in the "edit post" page. http://www.mathblogging.org/planetmo came out of a discussion on meta.MO, cf. http://meta.mathoverflow.net/discussion/1002/should-there-be-a-corner-for-discussion-close-to-mo/ 6. The Introduction "Introducing Myself" does not have any name. How does one know who is being introduced here? 7. Anonymous, the answer was only one click away, but why should you have to do that, so I've added some words at the start of the post so you know who I am. 8. David, thanks for adding the label!
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Projectile Motion with vector functions (3D Motion in space velocity) February 19th 2009, 01:53 PM Projectile Motion with vector functions (3D Motion in space velocity) A gun is fired with angle of elevation 30°. What is the muzzle speed if the maximum height of the shell is 484 m? g=gravity (9.8) What is the initial velocity? My instructor gave us a hint: v_0 is initial velocity. At max height vertical velocity = 0. This gives v_0 sin(alpha) - gt = 0. Vertical distance = -0.5 gt^2 + v_0 sin(alpha). Find v_0 from the above two equation. So I set those two equations equal to each other since they both equal zero. I'm not sure if I can do that. So my initial velocities cancelled out, I solved for t and got sqrt(2). I plugged that back into the vertical velocity and got v_0 = 28. I then plugged it back into the other equation to check it, but didn't get zero, I got 4.06. I'm pretty lost. February 19th 2009, 02:30 PM $v_0\sin{\alpha} - gt = 0$ $t = \frac{v_0\sin{\alpha}}{g}$ $\Delta y = v_0\sin{\alpha} \cdot t - \frac{1}{2}gt^2$ $\Delta y = v_0\sin{\alpha} \cdot \frac{v_0\sin{\alpha}}{g} - \frac{1}{2}g\left(\frac{v_0\sin{\alpha}}{g}\right) ^2$ $\Delta y = \frac{v_0^2 \sin^2{\alpha}}{g} - \frac{v_0^2 \sin^2{\alpha}}{2g}<br />$ $\Delta y = \frac{v_0^2 \sin^2{\alpha}}{2g}$ $v_0 = \sqrt{\frac{2g \Delta y}{\sin^2{\alpha}}}$
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Torelli theorems for kähler k3 surfaces Results 1 - 10 of 23 , 1996 "... Abstract. We consider derived categories of coherent sheaves on smooth projective varieties. We prove that any equivalence between them can be represented by an object on the product. Using this, we give a necessary and sufficient condition for equivalence of derived categories of two K3 surfaces. ..." Cited by 91 (6 self) Add to MetaCart Abstract. We consider derived categories of coherent sheaves on smooth projective varieties. We prove that any equivalence between them can be represented by an object on the product. Using this, we give a necessary and sufficient condition for equivalence of derived categories of two K3 surfaces. - I, Topology , 1993 "... (i) Topology of embedded surfaces. Let X be a smooth, simply-connected 4-manifold, and ξ a 2-dimensional homology class in X. One of the features of topology in dimension 4 is the fact that, although one may always represent ξ as the fundamental class of some smoothly ..." Cited by 68 (6 self) Add to MetaCart (i) Topology of embedded surfaces. Let X be a smooth, simply-connected 4-manifold, and ξ a 2-dimensional homology class in X. One of the features of topology in dimension 4 is the fact that, although one may always represent ξ as the fundamental class of some smoothly "... In this paper we propose a way to construct an analytic space over a non-archimedean field, starting with a real manifold with an affine structure which has integral monodromy. Our construction is motivated by the junction of Homological Mirror conjecture and geometric Strominger-Yau-Zaslow conjectu ..." Cited by 35 (3 self) Add to MetaCart In this paper we propose a way to construct an analytic space over a non-archimedean field, starting with a real manifold with an affine structure which has integral monodromy. Our construction is motivated by the junction of Homological Mirror conjecture and geometric Strominger-Yau-Zaslow conjecture. In particular, we glue from “flat pieces ” an analytic K3 surface. As a byproduct of our approach we obtain an action of an arithmetic subgroup of the group SO(1,18) by piecewise-linear transformations on the 2-dimensional sphere S 2 equipped with naturally defined singular affine - Geom. Funct. Anal , 2001 "... One main problem in the theory of irreducible holomorphic symplectic manifolds is the description of the ample cone in the Picard group. The goal of ..." Cited by 18 (7 self) Add to MetaCart One main problem in the theory of irreducible holomorphic symplectic manifolds is the description of the ample cone in the Picard group. The goal of - Nucl. Phys , 1999 "... hep-th/9810210 utfa-98/26 spin-98/4 ..." "... Given a variety over a number field, are its rational points potentially dense, i.e., does there exist a finite extension over which rational points are Zariski dense? We study the question of potential density for symmetric products of surfaces. Contrary to the situation for curves, rational points ..." Cited by 17 (5 self) Add to MetaCart Given a variety over a number field, are its rational points potentially dense, i.e., does there exist a finite extension over which rational points are Zariski dense? We study the question of potential density for symmetric products of surfaces. Contrary to the situation for curves, rational points are not necessarily potentially dense on a sufficiently high symmetric product. Our main result is that rational points are potentially dense for the Nth symmetric product of a K3 surface, where N is explicitly determined by the geometry of the surface. The basic construction is that for some N, the Nth symmetric power of a K3 surface is birational to an abelian fibration over P N. It is an interesting geometric problem to find the smallest N with this property. 1 - on T 6 ,” JHEP 0803 (2008) 022 arXiv:0712.0043 [hep-th "... For heterotic string theory compactified on T 6, we derive the complete set of T-duality invariants which characterize a pair of charge vectors (Q, P) labelling the electric and magnetic charges of the dyon. Using this we can identify the complete set of dyons to which the previously derived degener ..." Cited by 16 (9 self) Add to MetaCart For heterotic string theory compactified on T 6, we derive the complete set of T-duality invariants which characterize a pair of charge vectors (Q, P) labelling the electric and magnetic charges of the dyon. Using this we can identify the complete set of dyons to which the previously derived degeneracy formula can be extended. By going near special points in the moduli space of the theory we derive the spectrum of quarter BPS dyons in N = 4 supersymmetric gauge theory with simply laced gauge groups. The results are in agreement with those derived from , 2007 "... Abstract. We analyze the ample and moving cones of holomorphic symplectic manifolds, in light of recent advances in the minimal model program. As an application, we establish a numerical criterion for ampleness of divisors on fourfolds deformationequivalent to punctual Hilbert schemes of K3 surfaces ..." Cited by 9 (5 self) Add to MetaCart Abstract. We analyze the ample and moving cones of holomorphic symplectic manifolds, in light of recent advances in the minimal model program. As an application, we establish a numerical criterion for ampleness of divisors on fourfolds deformationequivalent to punctual Hilbert schemes of K3 surfaces. 1. , 909 "... Suppose X is a smooth projective complex variety. Let N1(X, Z) ⊂ H2(X, Z) and N 1 (X, Z) ⊂ H 2 (X, Z) denote the group of curve classes modulo homological equivalence and the Néron-Severi group respectively. The monoids of effective classes in each group generate cones ..." Cited by 9 (3 self) Add to MetaCart Suppose X is a smooth projective complex variety. Let N1(X, Z) ⊂ H2(X, Z) and N 1 (X, Z) ⊂ H 2 (X, Z) denote the group of curve classes modulo homological equivalence and the Néron-Severi group respectively. The monoids of effective classes in each group generate cones - Manuscripta Math "... Abstract. A rational Lagrangian fibration f on an irreducible symplecitc variety V is a rational map which is birationally equivalent to a regular surjective morphism with Lagrangian fibers. By analogy with K3 surfaces, it is natural to expect that a rational Lagrangian fibration exists if and only ..." Cited by 7 (1 self) Add to MetaCart Abstract. A rational Lagrangian fibration f on an irreducible symplecitc variety V is a rational map which is birationally equivalent to a regular surjective morphism with Lagrangian fibers. By analogy with K3 surfaces, it is natural to expect that a rational Lagrangian fibration exists if and only if V has a divisor D with Bogomolov–Beauville square 0. This conjecture is proved in the case when V is the punctual Hilbert scheme of a generic algebraic K3 surface S. The construction of f uses a twisted Fourier–Mukai transform which induces an isomorphism of V with a certain moduli space of twisted sheaves on another K3 surface M, obtained from S as its Fourier–Mukai partner. According to Beauville [Beau-1], [Beau-2], the d-th symmetric power S (d) of a K3 surface S has a natural resolution of singularities, the punctual Hilbert scheme S [d] = Hilb d S, which is a 2d-dimensional irreducible
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Enhanced Privacy ID Sketch of EPID Scheme We have developed two EPID schemes, one from the strong RSA assumption [7] and the other from bilinear maps [6]. In this article, we briefly sketch the EPID scheme from bilinear maps. (The full scheme can be found in [6]). Let us first review some background on bilinear maps. Let G1 and G2 be two multiplicative cyclic groups of prime order p. Let g1 be a generator of G1, and g[2] be a generator of G2. We say e: G1 x G2 → GT is an admissible bilinear map function, if it satisfies the following properties: For all u ∈ G1, v ∈ G2, and for all integers a, b, equation e(u^a, v^b) = e(u, v)^ab holds. The result of e(g[1]g[2] ) is a generator of GT. There exists an efficient algorithm for computing e(u, v) for any u ∈ G1, v ∈ G2. Our EPID scheme is derived from Boneh, Boyen, and Shacham's group signatures scheme [2] and has the following operations: Setup: The issuer does the following: 1. Chooses G1 and G2 of prime order p and a bilinear map function e : G1 x G2 → GT. 2. Chooses a group G3 of prime order p with generator g[3]. 3. Chooses at random g[1] h[1], h[2] ∈ G1 and g[2] ∈ G2. 4. Chooses a random r ∈ [1, p-1] and computes w = g[2]^r. The public key is (g[1], g[2], g[3], h[1], h[2], w) and the issuing private key is r. Join: The join protocol is an interactive protocol between the issuer and a member as follows: 1. The member chooses at random f and y' from [0, p-1] and computes 2. The member sends T to the issuer and performs the following proof of knowledge to the issuer: The issuer chooses at random x and y" from [0, p-1] and computes 3. The issuer sends (A, x, y" ) to the member. 4. The member computes y = y' + y"(mod p). The member's private key is (A, x, y, f ). Note that given a valid private key (A, x, y, f ), the following equation satisfies: Sign: Let (A, x, y, f ) be the member's private key. The member does the following: 1. If the random base option is used, the member chooses B at random from G3. 2. If the name base option is used, the member computes B = Hash (verifier's basename). Computes K = B^f Computes the following zero-knowledge proof This essentially proves that the member has a valid EPID private key issued by the issuer. 3. Computes the following zero-knowledge proof for each (B', K') pair in SIG-RL. This step proves that the member has not been revoked in SIR-RL; that is, the member did not create those (B', K') pairs in SIG-RL 4. Converts all the above zero-knowledge proofs into a signature by using the Fiat-Shamir heuristic [9]. Verify: Given the public key, PRIV-RL, SIG-RL, and an EPID signature, the verifier does the following: 1. If the random base option is used, the verifier verifies that B is an element in G3. 2. If the name base option is used, the verifier verifies that B = Hash (verifier's basename). 3. Verifies that K is an element in G3. 4. Verifies the following proof This step verifies that the member has a valid EPID private key. 5. Verifies that K ≠ B^f' for each f' in PRIV-RL. This step verifies that the member has not been revoked in PRIV-RL. 6. Verifies the following zero-knowledge proof for each (B', K') pair in SIG-RL. This step verifies that the member has not been revoked in SIG-RL. Comparison with Other Techniques There are other techniques to remotely authenticate hardware, and in this section we review these techniques and compare them with our EPID scheme. Public Key Infrastructure (PKI). Each hardware device has a unique public and private key pair as well as a device certificate. To authenticate hardware by using PKI, the device simply shows its certificate to the verifier along with a signature created by using the device's private key. As mentioned previously, this PKI approach does not satisfy the privacy requirement. Direct Anonymous Attestation (DAA). DAA was designed for anonymous attestation of TPM [4, 5]. DAA satisfies all the design requirements of remote hardware authentication; however, it has limited revocation capabilities compared to those of EPID. In the DAA scheme, there are two options for a balance between linkability and revocation. If the random base option is used, that is, a different base is used every time a DAA signature is performed, then any two signatures by a device are unlinkable, but revocation only works if the corrupted device private key has been revealed to the public. If a device has been compromised, but its private key has not been distributed to the verifiers (for example, if the corrupted device's private key is still under the control of the adversary), the corrupted TPM cannot be revoked. If the name base option is used, then any two signatures produced by a device, using the same base, are linkable. Thus, if the verifier determines that a device private key, used in a signature, has been compromised, that verifier can revoke that key locally; that is, the verifier can reject all future signatures generated by that private key, without knowledge of the compromised private key. However, the verifier cannot tell if a different verifier uses a different name base to revoke that private key, because when a different name is used, the revoked key cannot be identified. Furthermore, the name-based option does not safeguard privacy, because the verifier can link the transactions. Group Signatures (GS). A group signature scheme [1, 2] has similar properties to those of the EPID scheme. In a group signature scheme, an issuer creates a group public key and issues unique private keys to each group member. Each group member can use the private key to sign a message, and the resulting signature is called a group signature. The verifier can verify a group signature by using the group public key. Unlike EPID, group signature schemes have an additional property called traceability. This property enables the issuer to open any group signature and identify the actual group member who created the signature. In other words, a group signature is anonymous to the verifiers but not to the issuer. Again, as compared to this scheme, EPID keeps the identity of the group member from the issuer. Pseudonym System (PS). The pseudonym system [3], designed by Brands, can also be used for remote hardware authentication. In the pseudonym system, the display of a credential is anonymous by virtue of the fact that efficient zero-knowledge proof techniques are used for proving relations among committed values. To use the pseudonym system for hardware authentication, each hardware device obtains a credential from the issuer and uses the pseudonym credential for proof of membership. However, a credential in that system is linkable for multiple displays. To be unlinkable, a hardware device has to get multiple credentials from the issuer and use one credential at a time. This approach has limited application for hardware authentication, as the hardware device may never be able connect back to the issuer (the device manufacturer) once it has been produced. Thus, it cannot maintain the unlinkable property by continuing to get new credentials from the In Table 1, we summarize a comparison between different approaches to the remote hardware authentication problem. The EPID scheme is the only scheme that satisfies all the design requirements mentioned earlier. [1] G. Ateniese, J. Camenisch, M. Joye, and G. Tsudik. “A practical and provably secure coalition-resistant group signature scheme.” In Advances in Cryptology -- Crypto, Volume 1880 of Lecture Notes in Computer Science, pages 255–270, 2000. [2] D. Boneh, X. Boyen, and H. Shacham. “Short group signatures.” In Advances in Cryptology -- Crypto, Volume 3152 of Lecture Notes in Computer Science, pages 41–55, 2004. [3] S. Brands. Rethinking Public Key Infrastructures and Digital Certificates: Building in Privacy. MIT Press, Cambridge, MA, 2000. [4] E. Brickell, J. Camenisch, and L. Chen. “Direct Anonymous Attestation.” In Proceedings of the 11th ACM Conference on Computer and Communications Security, pages 132–145, 2004. [5] E. Brickell, L. Chen, and J. Li. “A New Direct Anonymous Attestation Scheme from Bilinear Maps.” In Proceedings of 1st International Conference on Trusted Computing, Volume 4968 of Lecture Notes in Computer Science, pages 166–178, 2008. [6] E. Brickell and J. Li. “Enhanced Privacy ID from Bilinear Pairing.” Cryptology ePrint Archive, Report 2009/095, 2009. [7] E. Brickell and J. Li. “Enhanced Privacy ID: a Direct Anonymous Attestation Scheme with Enhanced Revocation Capabilities.” In Proceedings of the 6th ACM Workshop on Privacy in the Electronic Society, pages 21–30, 2007. [8] J. Camenisch and V. Shoup. “Practical Verifiable Encryption and Decryption of Discrete Logarithms.” In Advances in Cryptology -- Crypto, Volume 2729 of Lecture Notes in Computer Science, pages 126–144, 2003. [9] A. Fiat and A. Shamir. “How to Prove Yourself: Practical Solutions to Identification and Signature Problems.” In Advances in Cryptology -- Crypto, Volume 263 of Lecture Notes in Computer Science, pages 186–194, 1987. [10] O. Goldreich, S. Micali, and A. Wigderson. “Proofs that Yield Nothing but their Validity.” Journal of the ACM, Volume 38(3), pages 690-728, 1991. [11] Trusted Computing Group. “TCG TPM Specification 1.2,” 2003, http://www.trustedcomputinggroup.org This article and more on similar subjects may be found in the Intel Technology Journal, June 2009 Edition, "Advances in Internet Security.
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Infinitely Divisible Matrices, Kernels, and Functions Infinitely Divisible Matrices, Kernels, and Functions Roger Alan Horn Department of Mathematics, Stanford University., 1967 - Matrices - 244 pages From inside the book 10 pages matching Schur product theorem in this book Where's the rest of this book? Results 1-3 of 10 What people are saying - Write a review We haven't found any reviews in the usual places. Related books Common terms and phrases 00 Theorem Chapter choice of arguments completely monotonic function completely monotonic sequence conformal mapping consistent choice continuous function continuous kernel Conversely Corollary cp(x Cq(S define diagonal difference quotient direct product divisible characteristic function divisible completely monotonic divisible positive definite dM(t dM(x dp(t dv(s dv(t equivalent finite function f graph Green's function Hermitian Hilbert space ij i,j=l implies incidence matrix inequality infinitely divisible characteristic infinitely divisible completely infinitely divisible kernels infinitely divisible positive integer interpolation problem irreducible component kernel K(x,y Krein-Milman theorem Lemma Let K(P,Q Let K(x,y limiting argument Loewner Lq(S n x n matrix nodes nonnegative quadratic form Pick's theorem polynomial principally infinitely divisible probability measure dp Proof prove real valued representation formula Schur product theorem semigroup stochastic process symmetric matrix teristic function Theorem 2.2 three point property unit disc univalent analytic function Bibliographic information Infinitely Divisible Matrices, Kernels, and Functions Roger Alan Horn Department of Mathematics, Stanford University., 1967 - Matrices - 244 pages
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Understanding RF power amplifiers | EE Times Design How-To Understanding RF power amplifiers The following is excerpted from Chapter 7 from a new edition of the book, RF Circuit Design, 2e by Christopher Bowick. (If you order a copy of this book before March 30, 2008 you can receive additional 20% off. Visit www.newnespress.com or call 1-800-545-2522 and use code 91603. ) Class-A Amplifiers and Linearity A class-A amplifier is defined as an amplifier that is biased so that the output current flows at all times. Thus, the input signal-drive level to the amplifier is kept small enough to avoid driving the transistor into cutoff. Another way of stating this is to say that the conduction angle of the transistor is 360deg., meaning that the transistor conducts for the full cycle of the input signal. The class-A amplifier is the most linear of all amplifier types. Linearity is simply a measure of how closely the output signal of the amplifier resembles the input signal. A linear amplifier is one in which the output signal is proportional to the input signal, as shown in Fig. 7-4. Notice that, in this case, the output signal level is equal to twice the input signal level, and the transfer function from input to output is a straight line. 7-4. Transfer characteristic for a linear amplifier. No transistor is perfectly linear, however, and, therefore, the output signal of an amplifier is never an exact replica of the input signal. There are always spurious components added to a signal in the form of harmonic generation or intermodulation distortion (IMD). These types of nonlinearities in transistors produce amplifier transfer functions that no longer resemble straight lines. 7-5. Nonlinear amplifier characteristics. Instead, a curved characteristic appears, as shown in Fig. 7-5A. The distortion caused to an input signal of such an amplifier is shown in Fig. 7-5B. Notice the flat topping of the output signal that occurs due to the second-harmonic content generated by the amplifier. This type of distortion is called harmonic distortion and is expressed by the equation: The second term of Equation 7-1 is known as the second harmonic or second-order distortion. The third term is called the third harmonic or third-order distortion. Of course, a perfectly linear amplifier will produce no second, third, or higher order products to distort the signal. Notice in Fig. 7-5, where the amplifier's transfer function is given as Vout =5V[in] +2V^2[in], that the second-order distortion component increases as the square of the input signal. Thus, with increasing input-signal levels, the second-order component will increase much faster than the fundamental component in the output signal. Eventually, the second-order content in the output signal will equal the amplitude of the fundamental. This effect is shown graphically in Fig. 7-6. 7-6. Second-order intercept point. The point at which the second-order and first-order content of the output signal are equal is called the second-order intercept point. A similar graph may be drawn for an amplifier which exhibits a third-order distortion characteristic. In this case, the third-order term is plotted along with the fundamental gain term of the amplifier. In this manner, the third-order intercept may be determined. The second- and third-order intercept of an amplifier are often used as figures of merit. The higher the intercept point, the better the amplifier is at amplifying large signals. When two or more signals are input to an amplifier simultaneously, the second-, third-, and higher-order intermodulation components are caused by the sum and difference products of each of the fundamental input signals and their associated harmonics. For example, when two perfect sinusoidal signals, at frequencies f1 and f2, are input to any nonlinear amplifier, the following output components will result: fundamental: f[1], f[2] second order: 2f[1], 2f[2], f[1] +f[2], f[1] - f[2] third order: 3f[1], 3f[2], 2f[1] ±f[2], 2f[2] ±f[1] +higher order terms Under normal circuit operation, the second-, third-, and higher-order terms are usually at a much smaller signal level than the fundamental component and, in the time domain, this is seen as distortion. Note that, if f[1] and f[2] are very close in frequency, the 2 f[1] - f[2] and 2[2] -f[1] terms fall very close to the two fundamental terms. Third-order distortion products are, therefore, much more difficult to eliminate through filtering once they are generated within an amplifier. The bias requirements for a class-A power amplifier are the same as those for small-signal amplifiers. In fact, the distinction between a class-A power amplifier and its small-signal counterpart is a hazy one at best. For all practical purposes, they are equivalent except for input and output signal levels.
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From Gerris Revision as of 14:13, 5 July 2012; view current revision ←Older revision | Newer revision→ The Hypre module makes available some features of the high-performance preconditioning library Hypre, in particular its algebraic multigrid for use instead of Gerris' native multigrid solver for Poisson equations. There are some special notes on installing Hypre for use with Gerris. The parameters of the Hypre module can be tuned using an optional parameter block. For example GModule hypre { solver_type = boomer_amg precond_type = none relax_type = gs-j coarsening_type = cgc_e cycle_type = 1 nlevel = 0 verbose = 0 where the values are set to their default. The parameters are the type of solver to be used, the type of relaxation to use for the AMG solver, the coarsening algorithm to use for the AMG solver, the type of cycle to use for the AMG solver, the maximum number of multigrid levels for the AMG solver (setting this to zero will use the depth of the quad/octree), selects whether Hypre should print its own statistics. So far, only two types of solvers are available: the AMG solver, a preconjugate gradient solver. For the AMG solver various types of cycles can be used and several algorithms are available for relaxation and coarsening. Please refer to the documentation page of the Hypre library for more details on the different algorithms. The keywords for the different relaxation algorithms are: Jacobi or CF-Jacobi, Gauss-Seidel, sequential (very slow!), Hybrid: SOR-J mix off-processor, SOR on-processor with outer relaxation parameters (forward solve), Hybrid: SOR-J mix off-processor, SOR on-processor with outer relaxation parameters (backward solve), Hybrid: SSOR-J mix off-processor, SSOR on-processor with outer relaxation parameters, Hybrid: GS-J mix off-processor, chaotic GS on-node, Jacobi (uses Matvec), only needed in CGNR. The keywords for the different coarsening algorithms are: CLJP-coarsening - a parallel coarsening algorithm using independent sets, Classical Ruge-Stueben coarsening on each processor, followed by a third pass, which adds coarse points on the boundaries, Falgout coarsening (uses 1 first, followed by CLJP using the interior coarse points generated by 1 as its first independent set) , PMIS-coarsening (a parallel coarsening algorithm using independent sets, generating lower complexities than CLJP, might also lead to slower convergence), HMIS-coarsening (uses one pass Ruge-Stueben on each processor independently, followed by PMIS using the interior C-points generated as its first independent set), CGC coarsening by M. Griebel, B. Metsch and A. Schweitzer, CGC-E coarsening by M. Griebel, B. Metsch and A. Schweitzer. For compatibility with Gerris' default solver, the Hypre module also uses the following parameters, set using GfsApproxProjectionsParams and GfsProjectionParams: the convergence threshold, the minimum number of iterations, the maximum number of iterations, the number of relaxation sweeps on each level. Note that Hypre uses the RMS-norm of the residual to define its convergence tolerance criteria (rather than the maximum for Gerris). It also calculates the RMS-norm in a different way than Gerris. This is partly related to the fact that the Hypre module solves a linear probem for which each stencil has been non-dimensionalised by the size of the diagonal cell, whereas the residual norm in Gerris takes into account the volume of all the cells of the domain. Also, whereas Gerris calculates the norm of the residual only over all the cells of the domain, Hypre takes into accounts the ghost cells at the boundaries of the domain. To account partially for the difference, a correction factor defined as <math> \sqrt \right( \frac{ \sum_1^n cell_volume }{n} \left) </math> where n is the number of cells in the domain is used to rescale the norm residual calculated by Hypre.
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Got Homework? Connect with other students for help. It's a free community. • across MIT Grad Student Online now • laura* Helped 1,000 students Online now • Hero College Math Guru Online now Here's the question you clicked on: I need help ...!! Select an ordered pair from the choices below that is a solution to the following system of inequalities: 3x – 4y > 7 y < 2x + 3 a. (3, -3) b. No solution c. (-4, -1) d. (6, 3) • one year ago • one year ago Your question is ready. Sign up for free to start getting answers. is replying to Can someone tell me what button the professor is hitting... • Teamwork 19 Teammate • Problem Solving 19 Hero • Engagement 19 Mad Hatter • You have blocked this person. • ✔ You're a fan Checking fan status... Thanks for being so helpful in mathematics. If you are getting quality help, make sure you spread the word about OpenStudy. This is the testimonial you wrote. You haven't written a testimonial for Owlfred.
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Pine Hill, NJ Math Tutor Find a Pine Hill, NJ Math Tutor My name is Mrs. W. I have 14 years' experience teaching in New Jersey. 23 Subjects: including prealgebra, reading, English, writing ...During my time in college, I took one 3-credit course in Differential Equations. While I was studying, I worked in the Math Center at my college. This gave me the opportunity to tutor students in a variety of math subjects, including Differential Equations. 11 Subjects: including algebra 1, algebra 2, calculus, geometry ...While my Ph.D studies were focused in the analytical area, I have significant experience in both areas of organic chemistry and biochemistry as well. During my doctoral studies I was selected to participate in the National Science Foundation GK-12 program where I worked in the local high school ... 9 Subjects: including algebra 1, algebra 2, chemistry, geometry ...When I taught Algebra 2, I would take my students across the street to McDonald's and measure 3 points on the huge arch and show that it is a parabola. Creativity, practical applications, and fun are my trademarks. As my students would always say, "Geometry really is EVERYWHERE". 12 Subjects: including precalculus, algebra 1, algebra 2, geometry ...I currently teach life science which is the NJ state 7th grade curriculum. Students who need science tutoring generally need help in recalling vocabulary and general concept review. As a special education teacher I have been required to adapt curriculum helping students with recall and understand concepts. 10 Subjects: including prealgebra, reading, writing, biology Related Pine Hill, NJ Tutors Pine Hill, NJ Accounting Tutors Pine Hill, NJ ACT Tutors Pine Hill, NJ Algebra Tutors Pine Hill, NJ Algebra 2 Tutors Pine Hill, NJ Calculus Tutors Pine Hill, NJ Geometry Tutors Pine Hill, NJ Math Tutors Pine Hill, NJ Prealgebra Tutors Pine Hill, NJ Precalculus Tutors Pine Hill, NJ SAT Tutors Pine Hill, NJ SAT Math Tutors Pine Hill, NJ Science Tutors Pine Hill, NJ Statistics Tutors Pine Hill, NJ Trigonometry Tutors Nearby Cities With Math Tutor Bellmawr Math Tutors Berlin Township, NJ Math Tutors Clementon Math Tutors Erial, NJ Math Tutors Glassboro Math Tutors Laurel Springs, NJ Math Tutors Lindenwold, NJ Math Tutors Medford Township, NJ Math Tutors Pine Valley, NJ Math Tutors Stratford, NJ Math Tutors Voorhees Math Tutors Voorhees Kirkwood, NJ Math Tutors Voorhees Township, NJ Math Tutors Waterford Township, NJ Math Tutors West Berlin Math Tutors
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Kew Gardens Algebra 2 Tutor Find a Kew Gardens Algebra 2 Tutor ...Lastly, I feel comfortable teaching material in many different ways to ensure full understanding. In the past, for example, I've drawn pictures, sung songs, broken down information into bullet points, acted it out, made flash cards, and so many more! Whatever works best for the student works for me. 37 Subjects: including algebra 2, chemistry, physics, calculus ...Do you have a student whose progress in reading is slower than expected or uneven with unexpected weaknesses, such as reading comprehension? Does your child have difficulty with spelling? Do you have a student who has difficulties with writing such as generating or getting ideas onto paper, organizing writing and grammatical problems? 30 Subjects: including algebra 2, English, reading, writing ...I have extensive experience in teaching and tutoring. While I was in undergraduate school in China, I assisted the English teacher to help freshmen in Engineer School pass the National English Test level 4. My responsibility included leading English evening class twice a week, as well as checking students’ homework and answering questions after class. 20 Subjects: including algebra 2, calculus, prealgebra, precalculus ...Working with a student and creating a customized learning curriculum makes every new student a challenge and opportunity. SAT math seems daunting to many students at first, particularly after the first real test. It does not have to be. 16 Subjects: including algebra 2, geometry, algebra 1, GED ...My ability is to assist you primarily comes from five (5) points: 1. Knowledge of Content: I graduated and worked as an engineer for several years before transitioning to education then to entertainment. I have taken the classes and the tests, so I know what to expect. 2. 15 Subjects: including algebra 2, physics, geometry, accounting
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a "homological dimension" for embedding of manifolds up vote 7 down vote favorite Let $A\to B$ be a surjective map of commutative $k$-algebras, and suppose $C\to B$ is a free resolution of $B$ as an $A$-algebra, meaning that $C$ is a free non-negatively graded commutative $A$-algebra with a differential decreasing degree by 1, and the map to $B$ is a quasi-isomorphism (e.g. $C$ might be a Koszul-Tate resolution). Let $d(C)$ denote the highest degree of a generator of $C$ over $A$, and let $d(B,A)$ be the smallest possible value of $d(C)$ over all such $C$; it is a kind of non-linear version of homological dimension. I am particularly interested in the case when $A=C^\infty(M)$ and $B=C^\infty(S)$ for a closed embedding $S\hookrightarrow M$ of manifolds, in which case I denote the quantity above by $d(S,M)$. For instance, if $S$ is the zero locus of a generic section of a trivial vector bundle $E$ on $M$, $d(S,M)=1$ (just take the Koszul resolution), whereas if the bundle is not trivial but stably trivial, $d(S,M)=2$. In general, the value of $d$ is the higher the farther away $E$ is from being trivial, in a certain sense that can be made precise. My question is, has this invariant been studied before, and if so, is there a formula expressing it in terms of some known topological invariants? I'd be happy with the case when $M$ is itself a vector bundle and $S$ the zero section. N.B. Asking for $C$ to be merely projective over $A$ would yield a different value of $d$: e.g. one would have $d=1$ for the zero locus of a generic section of any vector bundle. In this case, higher values of $d$ would detect singularities. add comment Know someone who can answer? Share a link to this question via email, Google+, Twitter, or Facebook. Browse other questions tagged manifolds or ask your own question.
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Fairchilds, TX Science Tutor Find a Fairchilds, TX Science Tutor ...Usually when I tutor my focus has been in Science and Mathematics, but my minor in Creative Writing and passion for writing have also resulted in helping to proof read countless essays and papers. If there's a topic you're interested in but it isn't listed below contact me and there's a good cha... 29 Subjects: including biostatistics, physics, physical science, physiology ...I am on the President's Honor Roll and have a GPA of 3.73. I am graduating in May and pursuing a Masters degree. I have had three chemical engineering internships through which I have gained experiences in the field. 22 Subjects: including chemical engineering, physical science, physics, geometry ...I have also completed additional course work and independent study on learning differences such as ADD/ADHD. I've taught science in middle and elementary school throughout the Houston area. I've also presented hands on fun labs for school enrichment classes, summer camp and remedial work. 18 Subjects: including ACT Science, reading, physical science, ESL/ESOL ...A mastery of geometry is essential to understanding the next level of mathematics, and I have had many years of experience using and teaching geometry. This is the first named mathematics course and is very fundamental in almost every field of study. Without a strong mastery of prealgebra, every following math and science course will be very difficult. 5 Subjects: including chemistry, geometry, algebra 1, algebra 2 ...I later earned a Master's in biology and even worked as a microbiologist for three years. I took my passion for the sciences and combined it with my passion for helping youngsters succeed in the classroom. I have now been teaching biology and chemistry (mostly biology) for five years and have b... 2 Subjects: including biology, chemistry Related Fairchilds, TX Tutors Fairchilds, TX Accounting Tutors Fairchilds, TX ACT Tutors Fairchilds, TX Algebra Tutors Fairchilds, TX Algebra 2 Tutors Fairchilds, TX Calculus Tutors Fairchilds, TX Geometry Tutors Fairchilds, TX Math Tutors Fairchilds, TX Prealgebra Tutors Fairchilds, TX Precalculus Tutors Fairchilds, TX SAT Tutors Fairchilds, TX SAT Math Tutors Fairchilds, TX Science Tutors Fairchilds, TX Statistics Tutors Fairchilds, TX Trigonometry Tutors
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takeWhile, applied to a predicate p and a list xs, returns the longest prefix (possibly empty) of xs of elements that satisfy p: > takeWhile (< 3) [1,2,3,4,1,2,3,4] == [1,2] > takeWhile (< 9) [1,2,3] == [1,2,3] > takeWhile (< 0) [1,2,3] == [] takeWhile, applied to a predicate p and a ByteString xs, returns the longest prefix (possibly empty) of xs of elements that satisfy p. O(n) takeWhile, applied to a predicate p and a Text, returns the longest prefix (possibly empty) of elements that satisfy p. Subject to fusion. takeWhile, applied to a predicate p and a ByteString xs, returns the longest prefix (possibly empty) of xs of elements that satisfy p. O(i) applied to a predicate p and a sequence xs, returns the longest prefix (possibly empty) of xs of elements that satisfy p. O(i) applied to a predicate p and a sequence xs, returns the longest suffix (possibly empty) of xs of elements that satisfy p. takeWhileR p xs is equivalent to reverse (takeWhileL p (reverse xs)).
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Posts by Total # Posts: 696 For the piecewise function, find the values g(-8), 8(3), and g(8). g(x)={X+6,FOR X<=3 7-x, for x>3 For the piecewise function, find the values g(-8), 8(3), and g(8). g(x)={X+6,FOR X<=3 7-x, for x>3 The researcher structures the study by addressing three topics which include the research question, the researcher s perspective and also the sample selection. On the above sentence, do I need to put a colon after include, or is the sentence fine the way it is? Do I use a colon or a period at the end of the following sentence? According to the author of this article, the hypothesis is as follows How do you solve this problem 1 1/5 minus 3/8? i will like to make a word with these letter aaiemctmsh Ratios Math i need help with ratios in math Marine Biology Any ideas where I can read online articles about marine species and the different types of habitats along coastal beaches? whats limestone used for? What do algae, kelp, and seaweeds have in common? How are they different? CIS Microcomputers Application It could be a cookie................ I dont know what to make for a physics experiment? RE: Water If I boil water at home, when and how do I know I've boiled the water long enough to make distilled water? What is the difference between drinking water and distilled water? Can we make our own distilled water? Could you tell me which words in column A have the same vowel sound as the words in clumn B. Column A Column B Path Butter Here Weight Saw Trouble Wide Put Hit-------------- File Look Weird Stool Laugh Luck Taught Heat Cheese Table Prune Pronunciation Eye Pan Matter Thanks. Where can I download a bowling score sheet? how do I compute sales tax? $1,367.85. sales tax rate is 5.75%. also, how do I add in city tax? Where can I download free score-keeping sheets for bowling? math please help 12x^2y+18xy^2 and the answer is 6xy(2x+3y) how do you get that answer? I go to the Middletown High School and I lost the combination to my locker which has my Global Histoory textbook in it. I was hoping somebody would be kind enough to tell me what the questions are on page 26 numbers 3-7 and page 31 numbers 3-7. I realize that we might not have... science (graphing data) on the axis of my graph i want to have my scale begin with 100 and then count by tens to 300. can I just start with 100 or do i have to put in a symbol or something first? If so, what's the symbol? math 117 A garden area is 30 ft long and 20 ft wide. A path of uniform width is set around the edge. If the remaining garden area is 400 ft2, what is the width of the path? using the quadratic formula I did the following: Let x = distance between the inner rectangle and the outer bound... Life Science How did Mendel novel approach contribute to his success in describing how traits are inherited Thank you for using the Jiskha Homework Help Forum. Here are some sites for you: 1. http:// en.wikipedia.org/wiki/Heredity (at the bottom, be sure to click for additional information ... 17 simplify 3/(x-5) + 1/ 1 - 4/(x-5) The non-use of grouping symbols makes this sentence without meaning. The non-use of grouping symbols makes this sentence without meaning. 3/x-5 +1 / 1 - 4/x-5 = I never know how to write the problems so someone can understnad what I mean, s... 20 Divide: x^2 -49y^2/6x^2+42y divided by (x^2-7xy) = factor the first term. Multiply the first term by the inverse of the second.Combine terms. I will be happy to critique your work. (x-3)(x+5)/2(2x ^2) * 2x-10 /x^2 - 25 = x-3/2x^2 ? or am I missing it somewhere :You are not w... 22. solve x/($a) - x/($b) = c what is this? The world wonders. believe it or not this was actually a problem that I have been given to solve. Any suggestions as to how I accomplish this? subtract. express in simplest form 13x/30 - 4x/ 15 = factor the first denominator. Get a common denominator. Combine terms. I will be happy to critique your work. ok 13x/30 - 4x/ 15 = This is where I get lost, I know that I have to fins the LCD but when I do that it looks like... add:Express in simplest form 4x/(x^2 -18x +72) + 4/(x-6) factor the first denominator. Get a common denominator. Combine terms. I will be happy to critique your work. ok hers goes 4x/(x-6)(x-12) + 4/ (x-6)= 4x + 4/(x-6)(x -12) or am I completely lost? you factored correctly. Yo... subtract: express your answer in simplest form. 5x-3/6 - (x+3)/6 answer choices a) 4x-1 b) 2x-3/3 c) 2x/3 -1 d) 2x/3 show me hou to arrive at the correct answer get a common denominator. get a common denominator. I thought 6 was the common denominator, why can't I use it s... divide: x^2 + 2x -15/4x^2 divided by x^2-25/2x-10 answer choices a) x-3/2x^2 b) x + 3/2x^2 c) 2x^2/x + 3 d) 2x^2/x - 3 any your work is? any your work is? (x-3)(x+5)/4x^2 * 2x-1/x^2-25= x-3/2x^2 Subtract: express your answer in simplest form. 2/5 - y/y-2 answers a)-3y-2/y-2 b) -3y -2/5(4-2) c) -3y-4/5(y-2) d) -3y-4/y-2 The way you have written the problem, is 2/5 minus y^3. I dont think that is what you meant. Please use grouping symbols on fractions () or [] The way ... Simplify: 3/4/4/5 answer choices are: a) 3/5 b) 5/3 C) 15/16 d)16/15 How do I go about solving this fraction, please show me how to work this. 3/4 divided by 4/5 1. Invert the second fraction. 3/4 / 5/4 2. Multiply the numerators and denominators. What answer do you get? 15/16... During rush hour, Fernando can drive 20 miles using the side roads in the same time that it takes to travel 15 miles on the freeway. If Fernando's rate on the side roads is 9 mi/h faster than his rate on the freeway, find his rate on the side roads. What is the formula and... What values for x must be exclued in the following fraction? x + 5/ -1 a) 5 b)none c) 0 d)-5 and how do I find the answer? if this is (x+5)/-1, no values. if you had a term like 1/(x-s), hten when x was equal to s, that is not allowed (rule: exclude all zero solutions in the d... math 117 x/6- x/8=1 Find a common denominator for the two x-terms on the left. Then do the subraction to get x/? = 1 You do the rest. These are not hard questions math 117 x/(x-2)- (x+1)/x= 8/(x^2-2x) notice that x^2 - 2x factors to x(x-2), which are found as the denominators of the first two fractions. Multiply each term by x(x-2), the rest is easy. math 117 5/(x+6)+ 2/(x^2+7x+6)= 3/(x+1) Rewrite x^2 +7x +1 as (x+6)(x+1) Multiply both sides of the equation by that expression. You get 5(x+1) + 2 = 3(x+6) Multiply out the parentheses and combine similar terms. You will be left with a simple linear equation for x. math 117 2/(5 )=(x-2)/20 math 117 Kevin earned $165 interest for 1 year on an investment of $1500. At the same rate, what amount of interest would be earned by an investment of $2500? At the same rate of interest, and period, the interest earned will be proprtional to the original principle. Therefore, you can... math 117 A plane flies 720 mi against a steady 30 mi/h headwind and then returns to the same point with the wind. If the entire trip takes 10 h, what is the plane s speed in still air? math 117 Ariana took 2 h longer to drive 360 mi on the first day of a trip than she took to drive 270 mi on the second day. If her speed was the same on both days, what was the driving time each day? Use the same method indicated in my response to your previous post. Thanks for asking. math 117 A passenger train can travel 325 mi in the same time a freight train takes to travel 200 mi. If the speed of the passenger train is 25 mi/h faster than the speed of the freight train, find the speed of each. Speed = distance/time Therefore time = distance/speed. Assume the tim... If one half of one integer is subtracted from three fifths of the next consecutive integer, the difference is 3. What are the two integers? see other post. math 117 If one half of one integer is subtracted from three fifths of the next consecutive integer, the difference is 3. What are the two integers? i got 24 and 25. (3/5 of 25) - (1/2 of 24) = 3 (n+1)*3/5 - 1/2 n =3 Right? I will be happy to critique your thinking. I suggest start by ... math 117/algebra simplify comples fractions. w+3/4w-----w-3/2w it is w-3 over 4w over w-3 over 2w q/f divided by t/u is the same as q/f multiplied by u/t, or qu/ft Division is the reciprocal of multiplication. q/f divided by t/u is the same as q/f multiplied by u/t, or qu/ft Division is the re... math 117/ algebra Fungicides account for 1/10 of the pesticides used in the US. Insecticides account for 1/4 of all pesticides used in the US. The two ratio of herbicides to insecticides used in the US can be written 1/10 ÷ 1/4 . Write this ratio in simplest form. see the other post abou... math 117/algebra The combined resistance of two resistors R_(1 amd R_2 )in a parallel circuit is given by the formula R_(r= 1/(1/R_1 + 1/R_2 )) Simplify the formula. Help what is this talking about and how do I work it? find R as a function fo r`1 and r2. 1/R= 1/r1 + `1/R2 R= ??? Get a common ... mat 117/algebra 2/(5w+10 )- 3/(2w-4) please show me how to work this problem. I assume this is some sort of combine the fractions, as there is nothing equal to the sentence above. factor out 1/((5w+10)(2w-4)) 1/ ((5w+10)(2w-4)) * ( 2*(2w-4) - 3(5w+10) ) do the multiplication in the paren.. 1/(... 1)Refer to the triangle in the figure. Find an expression that represents its perimeter. lft side 3/4x, right side 5/x^2 third side 1/x^2. 2)Find the perimeter of the given figure. x/2x - 5 and 8/2x - 3. 3)The volume of the box is represented by (x^2 + 5x +6)(x + 5) Find the p... Factor completely. ax - ay + x^2 - xy please show me how to factor this problem a(x-y) + x(x-y) = (a+x)(x-y) find the value of the polynomial 8x - 6 when x = 1 and when x = -1 8(1) - 6= 2 8(-1) - 6= -8 -6 = is the answer -14 or -2 -8 -6 = -14 mat 117/ algebra My question is about scientific notations. Here is the problem. What I need clarification on is the power signs. When to add, subtract or multiply? (2.4 x 10^-5)(4 x 10^-4) is the anwer 9.6 x 10^-9 or 9.6 x 10^20 The answer is NOT 9.6 x 10^20. Rember your rules of exponents: w... If the sides of a square are increased by 3 cm, the area is decreased by 36 cm^2. What were the dimensions of the original square? Please show me the formula and how to work. That doesn't sound possible. If the sides of a square are increased, the area must also be increas... factor each polynomial completely. to begin, state which method should be applied to the first step, given the guidelines of this section. Then continue the exercise and factor each polynomial completely. 2p - 6q + pq - 3q^2 Please help, I don't know how or where to begin.... Rewrite the middle term as the sumof two terms and then factor completely. Please show me the formula and how to use it correctly. 12w^2 + 19w + 4 19w can be written as 16w + 3w. Those are the cross product terms when multiplying 4w times 4 and 3w times 1. That is a clue that ... Factor each expression a^2(b-c)-16b^2(b-c) Help show me how (b-c) appears in both terms and can be factored out, giving you (b-c)(a^2-16b^2) Now note that the second term can also be factored since it is the difference of two perfect squares. (a^2-16b^2) = (a+4b)(a-4b) Make th... Determine whetere each of the following trinomials is a perfect square. If it is, factor the trinomial. x^2 - 24x + 48 I cannot get the 24x I've tried (x-24)(x - 2) What am I doing wrong? It is not a square. THe factors are 21.797 and 2.20, approximately. mat 117/algebra Find a value for k so the 9m^2-kn^2 will have the factors 3m + 7n and 3m -7n. Please show me how to get this and show the work please. Use that (a-b)(a+b) = a^2 - b^2 So, you can read-off that k = mat 117/algebra Find all positive values for k which each for each of the following can be factored. (1) x^2 + x + k) k<= 1/4 Which species of Penguins is the largest? Check this site for the penguin species that's the largest. http://www.enchantedlearning.com/subjects/birds/printouts/penguins.shtml The area of a rectangle of length x is given by 3x^2 + 5x. Find the width of the rectangle. Show me the formula and how to use it please. area= length times width 3x^2 + 5x = x * width divide both sides by x, then you have width. mat 117/algebra Find the GCF of each product. Please show the steps so I can work the problem by myself. it is 6y squared - 3y (6y^2-3y)(y+7) 3y(2y-1)(y+7) 3y will be the greatest common factor, as each term when you multiply it out will have a 3y. In case you want to work it out.. 3y(2y^2+13... The price of an item is given by p=2xsquared - 100. Find the polymonial that represents the revenue generated from the sale of x items. Multiply the price term, 2x^2 - 100, by the number of sales, x. That should be the revenue from selling x units. The p(x) relationship you ha... math 117/algebra The US population 1990 was approximately 250 million, and the average growth rate for the past 30 years gives a doubling time of 66 years. The above formula for the US then becomes P(in millions) = 250 x 1(y - 1990)/66 (1) What will the population of the US be in 2025 if this ... math 117 algebra The cost i dollarsof manufacturing w wing nuts is given by the expression 0.07w + 13.3. Find the cost when 375 wing nuts are made. What is the average cost to manufacture one wing nut? Put in 375 for w, and compute the cost. Average cost= costabove/w I'm sorry this still i... 1) The length of one of the equal legs of an isisceles triangle is 8cm less than 4 time the length of the base. If the perimeter is 29 cm, find the length of one of the equal legs. a) 4 cm B) 5 cm C) 11 cm d) 12 cm 2) The perimeter of a rectangle is to be no greater than 300 i... The sum of tow numbers is 71. The second is 7 more than 3 time the first. What are the two numbers? let x = the smaller number then you know that 7+3x +x =71 solve for x Sally bought three chocolate bars and a pack of gum and paid $1.75. jake bought two chocolate bars and four packs of gum and paid $2.00. Find the cost of a chocolate bar nad the cost of a pack of gum. 3C + 1G= 1.75 2C + 4G=2.00 solve. I know that i have to eliminate the c'... Rewrite the equation -x -6y = -6 as a function of x. add x to both sides, add six to both sides. solve each of the following systems by substitution. 16) 5x -2y = -5 y - 5x = 3 20) 8x -4y = 16 y = 2x - 4 28) 4x -12y = 5 -x + 3y = -1 Step one: Solve on of the equations for one of the variables. y =2x-4 Step two:Substitute the expression for the variable found in step one in... if f(x= 5x - 1 find f(a-2) Please show me the work so I can understand how to arrive at the solution. Thank you. f(a-2)=5(a-2)-1 the inventor charges $4.00 per unit, then her profit for producing and selling x units is given by the function P(x) = 2.25x - 7000 (a) What is her profit if she sells 2000 units? (b) What is per profit if she sells 5000 units? (c) What is the break-even point for sales? (a) S... I have a graph that shows a ---- kind of 3 line above the solid line for x & y. My assignment is as follows. Whe have graphed the boundary line for the liear inequality. Determine the correct half-plane. y >3 First how do I solve and 2 how do I graph it? If the allowed area... How do you factor 3x^2-x-4? thanks in advance How do you factor 3x^2-x-4? thanks in advance 3 times what = 3? 3 of course. giving you (3x+/-a)(1x+/-b). a and b can only be 1 and 4 or 2 and 2. Can you take it from here? (3x-4)(x+1)? If you have steel and wood at 0 Celsius, which is colder Both are the same temperature. What are Active X controls? Are we supposed to "enable" or "disable" them? does not matter http://www.webopedia.com/TERM/A/ActiveX_control.html You have to use your judgment, depending on which program seems to be requiring it. What are the main points to consider when choosing a monitor? What is the footprint? The user's eye sight. Cost. There may be othrs. computer science Is there a website that explains computer terms and definitions? http://www.computeruser.com/resources/dictionary/ http://www.webopedia.com/ Another site from your first post is below. computer science Is there a website that explains computer terms and definitions? http://whatis.techtarget.com/ I don't know why you said it was perfectly inelastic when is not. Is relative elastic Which one is correct: As president Bush walked to rhe podium,... or As President Bush walked to the podium,.... Since that is his official title, it would be treated the same way as Mr., or Gen. Cap on Pres My thesis is: Our nation needs a health care plan capable of addressing the needs of each individual. My Question is: How can I make this into a powerful thesis staement? You could start out by indicating that there is a lack of adequate health care for many individuals in an ... Can you tell me what type of essay I would be writing in response to this statement: "What, if anything, is significant about an issue--expressed in a claim?" My instructor told us to write an essay to this question. A "claim" is usually the term for the th... can you tell me what direction to take with this? My essay: During the last century, the average life span of Americans nearly doubled, from 49 years in 1900 to nearly 80 years in 2000. Increased life expectancy and advances in U.S. healthcare means that Americans now live lon... Based on what I have so far, what direction do you think I should go--what do you feel the thesis is about? This will eventually end up 10 pages long. I am concerned that I will not find enough to write about. The assignment is, "What, if anything, is significant about an... Can you explain the differences in these terms, and the function they serve when writing an essay? thesis and thesis statement central reasoning and central relationship The thesis is your central idea, your main idea, the point you are trying to prove in your paper. The thesi... social science Is iot possible to find out the number of physicians in a given practice--per state? example: how many doctors have a practice in geriatrics in the state of Utah? http://www.ama-assn.org/cgi-bin/ sserver/datalist.cgi I found it by state and county, but not just by state. how can I send material that is only intended for teachers, instructors, etc..and not the world? i don't think you can. you have to copy and paste your material onto this forum and teachers will help you with it. I believe that's the only way. "anon" is right... May I submit my draft for an essay for your comments? Please put your draft on the board and one of the teachers will be glad to comment. Please don't post my question or your answer because I do not want others to steal my idea! The only way we have to communicate with you is by posting on our message boards. Sorry. =( I need to learn to type on A computer. http://www.bbc.co.uk/schools/typing/flash/stage1.s... Do you think it is truly possible to get all of the information I would need to write an essay about the sudden "halt" or end of production of electric cars? And, what about the Hybreds? I am apprehensive about this topic because I may not be able to find all there i... Is there a method of determining if you debit or credit an account? How do you know if you should debit or credit a transaction? If it's a balance sheet accout you need to learn (and mrmorize) which side of the equation i't on, and it's normal balance. Assets norma... which is saltier the gulf of mexico or pacific ocean http://www.windows.ucar.edu/tour/link=/earth/Water/images/salinity_big_gif_image.html&edu=high The more orange, the higher salinity Can you help me find out any information about this address? My security program identified it as a virus and promptly removed it. Can you help me identify it? ADW_WEBSEARCH.AS http:// answers.yahoo.com/question/index?qid=20060801013521AAUqfpo STay away from porn sites, this vi... The length of a rectangle is 5 in. more than twice its width.? How do I find the width of the rectangle. duplicate post Divide the length by 2 it's going to be a decimal The length of a rectangle is 5 in. more than twice its width.? How do I find the width of the rectangle. The length = (2 x width) + 5 inches. Do you have any other information about the rectangle such as the area or the perimeter. I don't think there is enough information ... Pages: <<Prev | 1 | 2 | 3 | 4 | 5 | 6 | 7
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prove M is complete December 3rd 2011, 05:15 PM #1 Senior Member Jan 2010 prove M is complete Suppose that every countable, closed subset of M is complete. Prove that M is complete. my idea is to show that M is closed first, then let (Xn) be a cauchy sequence in M, so it's cauchy in all of its subset and then converge, so M is complete. Re: prove M is complete But, $M$ may not be countable, so this doesn't work. Try proving that if $(x_n)$ is a Cauchy sequence then $X=\overline{\{x_n:n\in\mathbb{N}\}}$ contains at most one more element and thus is also countable. But, then $(x_n)$ is a Cauchy sequence in the countable closed subset $X\subseteq M$. Re: prove M is complete if A is subset of M, and (Xn) is cauchy in M, does it imply (Xn) is cauchy in A? Re: prove M is complete December 3rd 2011, 05:23 PM #2 December 3rd 2011, 05:45 PM #3 Senior Member Jan 2010 December 3rd 2011, 05:46 PM #4
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I’ve often heard it argued that learning maths is like learning another language. There is a whole vocabulary and a way of speaking that is alien to people who don’t live in the land of maths. Abstract concepts are understood by saying things that only maths people understand. The conjunction is the equals sign; verbs are operators; a degree-level literature essay is a second-order differential equation. If that’s true, then Fraction County is the kind of place where the banjo stops playing when you walk into a bar. The talking stops. The locals all put down their home-made moonshine and all that can be heard is the faint rustle of tumbleweed blowing along the street outside. And you realise that the language they were talking is a completely different dialect from one that you’ve understood It is no wonder that many children panic when they hear the word “fraction”. Think about this. The children walk into a room and see ¼ written on the board. The teacher asks “how do you say this?” A brave child sticks their hand up and says “one line four”. Another child, emboldened by the first contribution, suggests “one point four”. Then someone asks “is it a fourth?” “That’s not exactly how we say it,” corrects the teacher, obliquely referring to some shadowy group of people the children have never heard of. A group of people that obviously can already speak ‘Fraction’. “We say ‘quarter’” The teacher smiles reassuringly, but inside is concerned. She knows that the children should already be able to read and say a quarter and she utters a silent curse at the children’s previous teacher. The lesson continues. The children learn that fractions are something to do with pizza (or if you listen to Sal Khan, pie). Then, after seeing that ¼ of a pizza is one piece out of 4, the teacher holds up 4 multilink cubes that are all joined together in a small tower. She asks the children how many cubes are in the tower. The children say “four”. The teacher breaks off a cube. She asks how many cubes she broke off. The children say “one”. “Ah, but what fraction did I break off?” asks the teacher, with an air of mystery. “Half?” asks a child. “A third?” asks another. Ever patient, the teacher persists. “How many cubes were in the tower?” “So what is the ‘out of’ number?” “So this cube is one out of four,” declares the teacher triumphantly, writing ¼ on the board again. “How do we say that?” “One line four” says a child. “One four” says another. “Quarter” says a third. “Yes,” says the teacher, pouncing on the learning. She vigorously shakes the child in sheer joy that someone has got it. “And we write a quarter, one over four.” The problem is in the language. The children have already learned that division is one word that means two different things – sharing and grouping. Now there’s the whole same thing going on with fractions. They’re sharing pizzas and calling each piece a fraction. Then they’re grouping sets of objects into equal subsets and calling each subset a fraction. Then despite the fraction being called “a quarter”, the teacher describes it as being “one out of four” whilst explaining that you write it “one over four.” The concepts behind these aren’t impossible to grasp, but the language we use to describe them is just so inefficient. This is one of the reasons that my favourite thing to come out of the old National Numeracy Strategy was the book on maths vocabulary – describing the kind of words that children should be taught in each subsequent year. But knowing the words is only part of the problem. I know some French words and some Spanish words but (to my shame) I find it hard to put them in the right order. The language of ‘Fraction’ is similar. It takes practice and good teaching to put them in order. If your teacher is woolly in their teaching and you don’t practice enough, you won’t learn the language. Worse, I know plenty of people whose maths teacher lost patience with them during some maths lesson or the other and shouted at them for not getting it quickly enough. This is often a reflection on that teacher’s subject knowledge, not the maths ability of the student. It is a reason why I recommend Derek Haylock’s excellent book on teaching maths. So next time you’re on the road to Fraction County, make sure you’ve rehearsed some of your lines – you may just teach your child to know their denominators from their numerators. Good for the fractions learning; bad for the coffee mug Sometimes children hear the word 'fractions' and they turn off. I saw it on Wednesday when I started my lesson on comparing and ordering fractions. I had barely uttered the words when I saw a few heads drop. A few children joined in when I asked them what they knew about fractions – one knew the word 'third'; someone else knew 'part'; yet another one knew they have something to do with division. But quite a few heads with dropped. So while the keen had their hands up, and others were looking to avoid eye contact, I slid an empty coffee mug into an empty plastic bag. Then, for security, whilst the conversation continued, I placed the first plastic bag into a second one. Then I smacked it against the wall. Really hard. All the children looked – some jumped. I proceeded to pull pieces out of the bag and estimate how much of the mug each piece had been, from the large chunks (1/3 or 1/5) to the tiny chips that were only 1/1000 or maybe even smaller. The children were engaged and by the end of the lesson all of them had made some progress about ordering and comparing fractions. Even the special needs group children who, according to their data, struggle to order numbers 1-100. As a bonus, we even specified that the bottom of the fraction was called the denominator and the top number the numerator – I love it when children learn proper maths words, although it was amusing to hear one child call the top number the nominator and the bottom number the dominator. So, if you're stuck with teaching fractions – break something. At least you'll stop the heads from dropping… Valuing misconceptions on the way to explaining fractions I filmed this about 6 months ago, following an excellent session about fractions on the Mathematics Specialist Teacher Programme. The challenge that we were given, and then I in turn gave to the children, was given a 4-pint bottle of milk that gets 3/5 of a pint drunk each day, how many days does the milk bottle last for? Those of us with a formal background in maths would say: 4 ÷ 3/5 = 4 ÷ 3 x 5 = 4 x 5 ÷ 3 = 20 ÷ 3 = 6 r 2. So the milk lasts for 6 and a bit days. If we wanted to be really fancy we would say the milk lasts for 6 and 2/3 days. And isn't it more practical to say the milk lasts for 6 days and there's 2/5 of a pint left over? Does our understanding of the algorithms let us say that? Also can children, who are without the drilled-in knowledge that when you divide a divisor you actually multiply, do this question? That's what the video explores – and there's some interesting misconceptions on the way. Fractions: learning something new Yesterday was a complete surprise to me. I learnt something new about maths. And I enjoyed it. Without trying to show off, I do know a lot of maths. I won’t bore you with too many of the details, but I am both interested in maths and quite good at it. I recognise that there are a lot of people who are much better than me – without some of those people I would never have got through my ‘A’ level maths (thanks Greg, thanks Yao) nor my Engineering degree (thanks, Jim, thanks Dan). However, in primary teaching I haven’t met too many of those people. Most of my colleagues are good at teaching maths, but would say that it is not their main interest. Some would demonstrate an enthusiasm for a particular branch of maths, whilst a few would express some negativity about areas of maths, particularly at the higher levels of the primary age range. Yesterday’s topic at the local area meeting of the MAST programme was ‘fractions’ – an area of maths which usually generates the word ‘Hmph’ from children, parents and teachers alike. I was so excited by some of the fractions problems we attempted I took them straight back to school the next day and filmed my Year 6 children trying to solve them. Here’s the video: http://www.youtube.com/get_playerHopefully you can see how the children progressed in the lesson. Many of the children, despite being the most able in the school, had quite a negative attitude to solving problems involving fractions. Through using models and images the children now have a better conceptual understanding of fractions – they have linked the visual to the concrete – and are now ready to move on to using the abstract: numerical fractions themselves. It struck me that as teachers we often move too quickly from the concrete to the abstract. If the highest ability children needed this level of input to begin to ‘get it’, then younger children and less able will need far more input at the concrete and visual stage before they move on to the abstract. This makes complete common sense, but in our overly prescriptive curriculum, how often do we rush children on to using and failing with the numbers when they don’t get the concept? So if two and half men take two and half days to dig two and half trenches, how many trenches can one man dig in one day? My answer was one trench and I was completely wrong. The feeling was exquisite – some maths that I didn’t get. My table group had to work hard to try and solve the problem and we still didn’t get it. Finally when someone provided a solution and the concept started to sink in it was marvellous to realise that I had been challenged with something and learnt something new as a consequence.
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just an integral... Hi everyone! Could someone help me with evaluating the following integral? [itex]\int_{2 \pi /L}^{\pi/l_0} \int_{2 \pi /L}^{\pi/l_0} \frac{\cos(k_x \Delta x)}{k_x^2 + k_y^2} dk_x dk_y [/itex] I have a good reason to believe that it will end up with some [itex] \frac{1}{2} \ln (\frac{L}{\Delta x})[/itex] though this might just be some approximation of it, since [itex] l_0 \ll L, \Delta x \ll L[/itex] . Any help would be appreciated! Thank you!
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The plausibility of alternative placements for theropod taxa [Date Prev][Date Next][Thread Prev][Thread Next][Date Index][Thread Index][Subject Index][Author Index] The plausibility of alternative placements for theropod taxa • To: dinosaur@usc.edu • Subject: The plausibility of alternative placements for theropod taxa • From: Michael Mortimer <mickey_mortimer111@msn.com> • Date: Fri, 21 Mar 2008 03:55:38 -0700 • Reply-to: mickey_mortimer111@msn.com • Sender: owner-DINOSAUR@usc.edu • Sun-java-system-smtp-warning: Lines longer than SMTP allows found and wrapped. David Marjanovic wrote- >> I should try adding the holotype to a non-maniraptoriform supermatrix I've >> been working on (including all codings from Smith et al., 2007; Tykoski, >> 2005; Carrano and Sampson, 2007; Rauhut, 2003; Azuma and Currie, 2000; >> Allain, 2002; Ezcurra and Novas, 2006; etc.). > Wow. Is that supermatrix your thesis? Nah. As you know, ensuring a preexisting matrix is coded correctly and has objective character states takes as much time as creating your own matrix. So I would never use such a supermatrix for more than just seeing where the currently published matrices suggest taxa belong. I made it because I was curious about ceratosaur and coelophysoid monophyly. So far it contains all the characters, taxa and codings from- Smith et al.'s (2007) large theropod matrix in the Cryolophosaurus paper. (347 Tykoski's (2005) matrix focusing on coelophysoids and ceratosaurs from his thesis. (95 additional characters) Carrano and Sampson's (2007) ceratosaur matrix. (39 additional characters) Excurra and Novas' (2006) matrix focusing on coelophysoids from their Zupaysaurus paper. (61 additional characters) Rauhut's (2003) theropod matrix, including Xu et al.'s (2006) codings for Guanlong and Dilong, Lamanna's (2004) codings for Megaraptor, and Yates' (2005) codings for Dracovenator and several other taxa. (20 additional characters) Allain's (2002) matrix focusing on spinosauroids and carnosaurs from his Dubreuillosaurus paper (7 additional characters) Azuma and Currie's (2000) matrix from their Fukuiraptor paper (31 additional characters), which is basically the same as Currie and Carpenter's (2000) Acrocanthosaurus paper. Langer and Benton's (2006) matrix of basal dinosaur relationships (25 additional characters). Yates' (2006) sauropodomorph matrix (134 additional characters so far), in order to get good representation of the theropod sister group. I only checked character accuracy when two matrices disagreed, and generally didn't code taxa for characters nobody else had. Thus while superior to the studies listed above, it's by no means a finished product and represents more of a compilation of prior work than my own work. Coding 131 taxa for 763 characters the proper way is too large a project for me at the moment- that's what my coelurosaur analysis is and it's taking years. :) Obvious future steps include adding Holtz et al.'s (2004), Carrano et al.'s (2005), Sereno et al.'s new carcharodontosaurid stuff, and the info from the Lophostropheus, Tyrannotitan and Mapusaurus papers. Important taxa to add would be Scleromochlus, Lewisuchus, Sacisaurus, Eucoelophysis, Agnostiphys, Chindesaurus, Sarcosaurus, Chuandongocoelurus, Berberosaurus, Brontoraptor, Spinosaurus, Marshosaurus, Erectopus, Gasosaurus, Lourinhanosaurus, Yangchuanosaurus, Mapusaurus, Saurophaganax, Huaxiagnathus, Sinocalliopteryx, Tanycolagreus, Eotyrannus, Aniksosaurus, Juravenator, Nedcolbertia, Nqwebasaurus, Santanaraptor and Scipionyx. Also, coding Falcarius, Protarchaeopteryx, Incisivosaurus, Sinovenator, Mei, Buitreraptor and/or Rahonavis in addition to the two birds and two derived dromaeosaurids would quite probably affect the placement of Ornitholestes and Bagaraatan. Current results are- `--+--Ornithischia (5 taxa) |--Sauropodomorpha (4 taxa) | `--Herrerasaurus | | |--Dilophosaurus wetherilli | | |--"Dilophosaurus" sinensis | | `--Cryolophosaurus | `--+*-Gojirasaurus | |--Lophostropheus | |--Liliensternus | |--Zupaysaurus | `--+*-Shake'n'Bake taxon | |--+--Segisaurus | | `--"Syntarsus" kayentakatae | `--+--Coelophysis | `--+--Megapnosaurus | `--Procompsognathus | | `--Spinostropheus | `--+--Ceratosaurus | `--+--+--Noasaurus | | |--Genusaurus | | |--Masiakasaurus | | `--Laevisuchus | `--+--Ekrixinatosaurus | |--Rugops | `--+--Abelisaurus | `--+--+--Rajasaurus | | |--Majungasaurus | | `--Indosuchus | `--+--Ilokelesia | `--+--Aucasaurus | `--Carnotaurus | `--+--+--+--Eustreptospondylus | | `--+--Piveteausaurus | | |--Dubreuillosaurus | | `--Afrovenator | `--+--Torvosaurus | `--+--Chilantaisaurus | |--Irritator | |--Baryonyx | `--Suchomimus | |--Megaraptor | |--Carcharodontosaurus | `--Giganotosaurus | `--+--Acrocanthosaurus | `--+--Allosaurus | `--Sinraptor | `--+--Stokesosaurus | `--Tyrannosaurus | |--Mirischia | `--Aristosuchus | `--Coelurus | `--+--Compsognathus | `--Siamotyrannus `--+--Ornithomimosauria (2 `--Paraves (4 taxa) I forced various constraint trees to estimate the rough liklihood that alternative hypotheses are correct. I tried to test as many possibilities as I could recall were ever suggested in the last thirty years, with some older ones in there for good measure. Of course, with near certain coding errors, not every taxon coded for every character possible, and missing characters and taxa, these numbers shouldn't be taken as the final word. But a topology that needs 5 more steps is far more likely to be true than one that needs 20 more steps. So, starting with the most likely alternatives and working to the the least likely ones, with my subjective divisions of how liklihood correlates to extra steps in the trees... Extremely possible- The current tree, with the following non-consensus aspects- Silesaurus as a basal saurischian. Never suggested before, but all the data from Langer and Benton (2006) which kept it out of Dinosauria was included. Eoraptor and herrerasaurids as successively closer outgroups to Avepoda, as suggested by Sereno et al. (1993). This despite the fact Langer and Benton's data were included. Dilophosaurids as coelophysoids, as in Paul (1988) and most cladistic analyses. With Rauhut (2003), Yates (2005) and Smith et al. (2007) all contributing to the data, it certainly seems to support coelophysoid dilophosaurids. "Syntarsus" kayentakatae being closer to Segisaurus than to Megapnosaurus, as suggested by Tykoski (2005). Spinostropheus clading with Elaphrosaurus to the exclusion of other ceratosaurs, as in Lapparent (1960) and Carrano and Sampson (2007). Ceratosaurus closer to abelisauroids than Elaphrosaurus is, as in Holtz (2000). Ilokelesia being a carnotaurine, as in Carrano and Sampson (2007). Streptospondylus being a basal tetanurine outside the Spinosauroidea+Avetheropoda clade, which hasn't been suggested before. Poekilopleuron being a basal spinosauroid, which has not been suggested before. Torvosaurus being closer to spinosaurids than to eustreptospondylids, as in Rauhut (2003). The generally basalmost tetaurines Piatnitzkysaurus, Condorraptor, Xuanhanosaurus and "Szechuanoraptor" being closer to avetheropods than spinosauroids are. This has been suggested previously for Piatnitzkysaurus (Novas, 1992) and "Szechuanraptor" (Chure, 2000). Monolophosaurus being outside Avetheropoda, as in Smith et al. (2007). Carcharodontosaurids being outside Avetheropoda, as in Coria and Salgado (1995). Sinraptor being closer to Allosaurus than to Neovenator or Acrocanthosaurus, which I don't think has been suggested before. Neovenator being closer to allosaurids than carcharodontosaurids, as in Hutt et al. (1996). Acrocanthosaurus being closer to allosaurids than carcharodontosaurids, as in Stovall and Langston (1950). Fukuiraptor being a coelurosaur, as in Longrich (2001). Deltadromeus being a tyrannosauroid, which hasn't been suggested yet. Though the possibly synonymous Bahariasaurus has (Paul, 1988; Chure, 2000). Dilong being closer to birds than tyrannosaurids, as in Turner et al. (2007). This leaves no reason to postulate secondarily featherless tyrannosaurids. Mirischia and Aristosuchus being closer to Dilong than Compsognathus (as in Niaish, online 2006; though he had Dilong as a tyrannosauroid). Guanlong being closer to birds than tyrannosaurids (and Dilong!), which hasn't been suggested before and is frankly the opposite of what I expected. Siamotyrannus being a compsognathid, which hasn't been suggested before. Bagaraatan being a maniraptoran, as in Rauhut (2003). Forcing Elaphrosaurus to be closer to abelisaurids than Ceratosaurus is (as in Holtz, 1994) adds only one step. Forcing Streptospondylus to be sister to Eustreptospondylus (as in Allain, 2001) adds only one step. Streptospondylus moves into Spinosauroidea, whose topology remains the same. Forcing Piatnitzkysaurus to be outside the spinosauroid-avetheropod clade (as in Rauhut, 2003 and Smith et al., 2007) adds only one step. Condorraptor is its sister taxon in this case, as in Smith et al. (2007), and Xuanhanosaurus and "Szechuanoraptor" move along with it (as in Rauhut, 2003). Forcing Neovenator to be a carcharodontosaurid (as in Rauhut, 2003 and others) adds one step. The (Acrocanthosaurus(Sinraptor+Allosaurus)) clade remains, while Neovenator is the sister to Megaraptor in basal Carcharodontosauridae outside Avetheropoda. Forcing Siamotyrannus to be a carnosaur (Pharris, 1997) adds one step. The topology among paraphyletic carnosaurs is unchanged and it is a sinraptorid (which is where Pharris predicted it would be). Forcing Mirischia to be a compsognathid (as in Martill et al., 2000) adds one Forcing Coelophysis and Megapnosaurus rhodesiensis to be sister taxa (as in Tykoski, 2005 and others) adds 2 steps. Forcing Eustreptospondylus to be closer to spinosaurids than Torvosaurus (as in Smith et al., 2007) adds 2 steps. The other eustreptospondylids move with Forcing Poekilopleuron to be a torvosaurid (as in Galton and Jensen, 1979) adds 2 steps. The newly formed Torvosauridae are still sister to Spinosauridae. Forcing Chilantaisaurus to be a tyrannosauroid (as in Paul, 1988) adds 2 steps. Interestingly, this is rather close to where "Chilantaisaurus" maortuensis ends up. Forcing Allosauroidea (allosaurids, carcharodontosaurids and sinraptorids) (as in Sereno et al., 1996) to be monophyletic adds 2 steps. The topology within it stays the same, so that carcharodontosaurids are most basal and Sinraptor is nested within allosaurids. Monolophosaurus is still basal to Avetheropoda, while Fukuiraptor and Siamotyrannus are coelurosaurs. Forcing Monolophosaurus to be a spinosauroid (as suggested by Headden on the DML, 2002) adds 2 steps. It is the most basal spinosauroid in these trees. Forcing Fukuiraptor to be sister to Siamotyrannus (as in Holtz et al., 2004) adds 2 steps. The two are basal coelurosaurs outside Tyrannoraptora. Forcing Procompsognathinae sensu Sereno (Procompsognathus + Segisaurus) (as in Sereno and Wild, 1992) adds 3 steps. Forcing Dracovenator to be closer to Ceratosauria + Tetanurae than to Coelophysoidea (as in Yates, 2005) adds 3 more steps. Oddly, it ends up as a spinosaurid, while Cryolophosaurus is sister to Ceratosauria+Tetanurae and "Dilophosaurus" sinensis is a basal tetanurine. Dilophosaurus wetherilli stays in Coelophysoidea. Forcing Deltadromeus to be a ceratosaur (as suggested by Sereno et al., 2002) adds 3 more steps. It falls in the Elaphrosaurus + Spinostropheus clade. Forcing Carnotaurus and Majungasaurus to clade to the exclusion of Rajasaurus (as in Wilson et al., 2003) adds 3 steps. Forcing Sinraptoridae to be basal to Avetheropoda (as in Paul, 1988) adds 3 steps. In this tree, carcharodontosaurids are coelurosaurs. Forcing Fukuiraptor to be a carnosaur (as in Azuma and Currie, 2000 and Holtz et al., 2004) adds 3 more steps. It is placed sister to Allosaurus, while carcharodontosaurids and Monolophosaurus are still outside Avetheropoda. Forcing Aristosuchus to be a coelurid (as in Lydekker, 1889) adds 3 steps. In this tree, Guanlong is also a coelurid. Forcing Coelurus to be a compsognathid (as in Lull, 1911; technically, Compsognathus would be a coelurid...) adds 3 steps. Forcing Eusaurischia to exclude herrerasaurids and Eoraptor (as in Langer and Benton, 2006) adds only 4 more steps. These trees have the same topology as Langer and Benton's paper, with Silesaurus outside Dinosauria, Eoraptor closer to eusaurischians than herrerasaurids are, and Guaibasaurus as a basal theropod. Forcing Procompsognathus to be the most basal avepod (as in Paul, 1988) adds 4 Forcing Cryolophosaurus to be a basal tetanurine (as in Smith et al., 2005) adds 4 more steps. In these trees, "Dilophosaurus" sinensis is its sister Forcing Piatnitzkysaurus to be a spinosauroid (as in Holtz et al., 2004) adds 4 steps. It falls out (often with Condorraptor) as the basalmost spinosauroid, even more basal than Poekilopleuron. Forcing Neovenator to be the sister taxon to Allosaurus (as in Hutt et al., 1996) adds 4 steps. Acrocanthosaurus, Sinraptor and Megaraptor form successive outgroups, while carcharodontosaurids are coelurosaurs. Forcing Coelurus to be a maniraptoran (as in Gauthier, 1986) adds 4 steps. It is directly basal to Ornitholestes in this tree. Forcing Proceratosaurus to be sister to Ornitholestes (as in Paul, 1988) adds 4 steps. This pairing ends up in basal Maniraptora. Forcing Megapnosaurus rhodesiensis and "Syntarsus" kayentakatae to be sister taxa (as in Rowe, 1989) adds 5 more steps. In these trees, Procompsognathus is closest to Megapnosaurus sensu lato, with Coelophysis one step further out. Segisaurus is now in the Zupaysaurus-Liliensternus mess. Forcing Deltadromeus to be sister to ornithomimosaurs (as in Rauhut, 2003) adds 5 more steps. Forcing Spinostropheus to be sister to abelisaurs (but keeping Elaphrosaurus as the basalmost ceratosaur; as in Sereno et al., 2004) adds 5 more steps. Forcing Megaraptor to be a spinosauroid (as suggested by Calvo et al., 2004) adds 5 steps. It ends up sister to Torvosaurus+Spinosauridae. Forcing Siamotyrannus to be a tyrannosauroid (as in Buffetaut et al., 1996) adds 5 steps. Guanlong and Dilong are still closer to birds than to Forcing Bagaraatan to be a tyrannosauroid (as in my analyses from 2003 onward) adds 5 steps. Forcing Torvosaurus to be closer to eustreptospondylids than to spinosaurids (as in Sereno et al., 1994) adds 6 steps. In these trees, the four 'basalmost tetanurines' (Piatnitzkysaurus, Xuanhanosaurus, Condorraptor and "Szechuanoraptor") all move outside the spinosauroid-avetheropod clade. Forcing Afrovenator to be outside the Eustreptospondylus + Torvosaurus + Spinosauridae clade (as in Sereno et al., 1994) adds 6 steps. Dubreuillosaurus and Piveteausaurus stay with Afrovenator, and Torvosaurus is still closer to spinosaurids than Eustreptospondylus. Forcing Monolophosaurus to be a carnosaur (as suggested by Zhao and Currie, 1993) adds 6 steps. It is the basalmost carnosaur, and the topology of Allosauroidea is the same as when its monophyly is forced, with Fukuiraptor and Siamotyrannus still coelurosaurs. Forcing Ornitholestes to be a coelurid (as in Matthew and Brown, 1922) adds 6 Forcing Ornitholestes to be outside Maniraptoriformes (as in Paul, 1988) adds 6 Forcing Proceratosaurus to be a tyrannosauroid (as suggested by me on the DML) adds 6 steps. Forcing Dilophosaurus to be sister to Ceratosauria + Tetanurae (as in Rauhut, 2003) adds 7 more steps. In these trees, Dracovenator is sister to Dilophosaurus, while "Dilophosaurus" sinensis and Cryolophosaurus form a clade one node closer to ceratosaurs+tetanurines. Forcing Deltadromeus to be a noasaurid (as in Wilson et al., 2003) adds 7 more Forcing Xuanhanosaurus to be a torvosaurid adds 7 steps. Forcing Acrocanthosaurus to be a carcharodontosaurid (as in Sereno et al., 1996) adds 7 steps. In these trees, Neovenator is a more basal carcharodontosaurid, while Sinraptor and Allosaurus form a clade sister to Carcharodontosauridae. Monolophosaurus and Megaraptor are outside Avetheropoda, Fukuiraptor and Siamotyrannus are coelurosaurs, and Tyrannotitan is basal to Carcharodontosaurus+Giganotosaurus. Forcing Guanlong (as in Xu et al., 2006), Dilong (as in Xu et al., 2004) and/or Mirischia (as in Naish, online 2006) to be tyrannosauroids adds 7 steps. They form a clade with Aristosuchus to the exclusion of Tyrannosauridae, with "Alashansaurus" as the basalmost tyrannosauroid. Forcing Compsognathus to be outside Tyrannoraptora (as in Holtz, 1994) adds 7 Forcing Proceratosaurus to be basal to Coelurus and tyrannosauroids (as in Holtz, 2000) adds 7 steps. Possible but not well supported- Forcing Liliensternus to be more closely related to Dilophosaurus than to Coelophysis (as in Paul, 1988) adds 8 steps. Dracovenator (and sometimes Lophostropheus) joins this 'halticosaur' clade, while Zupaysaurus and Gojirasaurus stay closer top Coelophysis. Cryolophosaurus and "Dilophosaurus" sinensis are then closer to Ceratosauria+Tetanurae. Forcing "Szechuanoraptor" to be an allosaurid (as in Molnar et al., 1990) adds 8 steps. Forcing Afrovenator to be closer to Avetheropoda than Piatnitzkysaurus, Torvosaurus, Eustreptospondylus and Spinosauridae (as in Holtz, 2000) adds 8 steps. Dubreuillosaurus and Piveteausaurus stay in Spinosauroidea. Forcing spinosauroids to be carnosaurs (as in Rauhut, 2003 and older sources with more extensive Carnosauria's) adds 8 steps. Fukuiraptor also falls out in this clade, though Siamotyrannus remains a coelurosaur. Forcing Zupaysaurus to be closer to ceratosaurs+tetanurines than to coelophysoids (as in Arcucci and Coria, 1997) adds 9 steps. As in that study, dilophosaurids end up even closer to birds. Forcing Piatnitzkysaurus to be a basal carnosaur (as in Harris, 1998) adds 9 Forcing Coelurus to be a tyrannosauroid (as in Senter, 2007) adds 9 steps. The topology is similar to when Guanlong is forced to be a tyrannosauroid, with Coelurus outside the Dilong+Guanlong+Aristosuchus+Mirischia clade. Forcing Coelurus to be basal to tyrannoraptorans (as in Makovicky, 1995) adds 9 Forcing Bagaraatan to be outside Tyrannoraptora (as in Holtz, 2000) adds 9 Forcing Proceratosaurus to be a ceratosaurid (as in Huene, 1926) adds 9 steps. Forcing "Szechuanoraptor" to be a sinraptorid (as in Paul, 1988) adds 10 steps. Forcing Piatnitzkysaurus to be a eustreptospondylid (as in Paul, 1988) adds 10 steps. It ends up sister to other eustreptospondylids. Forcing Sinraptor to be basal to allosaurids and carcharodontosaurids within Allosauroidea (as in Harris, 1998) adds 10 steps. Oddly, this forces spinosauroids to be carnosaurs, in addition to Monolophosaurus. While Neovenator and Acrocanthosaurus are carcharodontosaurids, Fukuiraptor is an Forcing Dilong to be a compsognathid (as suggested by Olshevsky I believe, online) adds 10 steps. Forcing Eoraptor to be a basal theropod, but herrerasaurids to be outside Eusaurischia (as in Ezcurra, 2006) adds 11 steps. Forcing Indosaurus to be a tyrannosaurid (as in Chatterjee, 1978) adds 11 steps. Forcing Coelurus to be basal to avetheropods (as in Paul, 1988) adds 11 steps. Oddly, instead of being just outside Avetheropoda, it moves to the base of the Tetanurae with Tugulusaurus. Forcing Aristosuchus to be a compsognathid (as in Naish, 2002) adds 12 steps. Forcing Tyrannosaurus to be a maniraptoran (as in Sereno, 1997) adds 12 steps. Forcing coelophysoids to be ceratosaurs (as in Gauthier, 1986) adds 13 more steps. In these trees, Cryolophosaurus and "Dilophosaurus" sinensis are basal Forcing Elaphrosaurus to be a coelophysoid (as in Paul, 1988) adds 13 more steps. It falls out with Spinostropheus between Liliensternus+Lophostropheus and Zupaysaurus+derived coelophysids. Amusingly right where Paul put it. Forcing spinosaurids to be more basal than Piatnitzkysaurus, Eustreptospondylus, Afrovenator and Torvosaurus (as in Holtz, 2000) adds 13 steps. Spinosauroidea becomes paraphyletic to Avetheropoda, with Torvosaurus, Eustreptospondylidae, Poekilopleuron and Piatnitzkysaurus successively closer to it. Forcing Sinraptor to be closer to carcharodontosaurids than to Allosaurus (as in Coria and Currie, 2002) adds 13 steps. I these trees, Neovenator and Acrocanthosaurus are carcharodontosaurids, while Allosaurus is the basal Forcing Compsognathus to be a tyrannosauroid (as in Olshevsky, 1991) adds 13 steps. This also makes Sinosauropteryx, Guanlong, Coelurus, Dilong, Mirischia and Aristosuchus tyrannosauroids. Forcing Ilokelesia to be outside Noasauridae+Abelisauridae (as in Coria and Salgado, 2000) adds 14 steps. Forcing Afrovenator to be sister to Allosauroidea (as in Rauhut, 2003) adds 14 steps. Dubreuillosaurus and Piveteausaurus stay in Spinosauroidea. Forcing Ornitholestes outside Tyrannoraptora (as in Holtz, 1994 and others) adds 14 steps. Forcing Procompsognathus to be outside Dinosauria (as in Allen, 2004) adds 15 Forcing Deltadromeus to be closer to birds than Ornitholestes (as in Sereno et al., 1996) adds 15 more steps, mainly from moving Ornitholestes down the tree. Forcing Piatnitzkysaurus to be an allosaurid (as in Molnar et al., 1981) adds 15 steps. Near certainly untrue- Forcing Ceratosaurus to be closer to tetanurines than abelisaurids are (as in Carrano and Sampson, 1999) adds 18 steps. Elaphrosaurs and noasaurids stay with abelisaurids. Forcing Compsognathus outside Avetheropoda (as in Paul, 1988) adds 18 steps. Forcing Piatnitzkysaurus to be an abelisaur (as in Currie and Zhao, 1993) adds 21 steps. Forcing Monolophosaurus to be sister to Guanlong (as suggested by Carr, 2006) adds 22 steps. The pair are placed as coelurosaurs just outside Tyrannoraptora. Forcing Cryolophosaurus to be a carnosaur (as in Sereno et al., 1996) adds 23 more steps. It changes the tree a lot, with most basal tetanurines moved into Forcing Monolophosaurus to be a tyrannosauroid (as suggested by me on the DML) adds 24 steps. In these trees, Guanlong and Dilong are still closer to birds than to tyrannosaurids, though Siamotyrannus is a tyrannosauroid. Forcing Guanlong to be a carnosaur (as in Carr, 2006) adds 24 steps. Siamotyrannus, Fukuiraptor, Dilong and Aristosuchus are also carnosaurs in these trees. Forcing Tyrannosaurus to clade with ornithomimosaurs (as in Huene, 1923) adds 24 steps. Forcing Torvosaurus to be a ceratosaur (as in Britt, 1991) adds 26 steps. It emerges outside the elaphrosaur-ceratosaurid-abelisauroid clade, but other spinosauroids stay in Tetanurae. Forcing Guanlong to be a carnosaur sister taxon to Monolophosaurus (as in Carr, 2006) adds 27 steps. Forcing Acrocanthosaurus to be a spinosaurid (as in Walker, 1964)adds 30 steps. Spinosaurids are moved into Carnosauria. Forcing Elaphrosaurus to be an ornithomimosaur (as in Galton, 1982) adds 33 Forcing abelisaurids to be sister to carcharodontosaurids (as in Novas, 1997) adds 35 steps. The clade ends up in Ceratosauria, and Acrocanthosaurus and Neovenator remain in Carnosauria. Forcing Zupaysaurus to be a tetanurine (as in Arcucci and Coria, 2003) adds 37 Forcing Megaraptor to be a dromaeosaurid (as suggested in Rauhut, 2003) adds 38 Forcing Abelisaurus to be a carcharodontosaurid (as suggested by Lamanna et al., 2002) adds 39 steps. Forcing Monolophosaurus to be an ornitholestiid (as in Paul, 2002) adds 40 steps. Ornitholestes and Proceratosaurus are moved outside Avetheropoda with Forcing Ornitholestes to be an allosaurid (as in Paul, 1988) adds 41 steps. Forcing Sinosauropteryx outside Coelurosauria (as in Longrich, DML 2000) adds 42 steps. Forcing the less extensive Carnosauria of Molnar et al., 1990 (Piatnitzkysaurus, Allosaurus, carcharodontosaurids and tyrannosaurids) adds 44 steps. Spinosauroids, Monolophosaurus and Sinraptor form successively closer outgroups to Carnosauria. The Allosauridae of Molnar is paraphyletic to tyrannosaurids, with Piatnitzkysaurus most basal and carcharodontosaurids most closely related. Russell and Dong's (1993) crazy topology of adds 45 steps, mainly from moving ornithomimosaurs so basally. Bakker et al.'s (1988) topology of (Cerato(Allo(Dromaeo(Acrocantho(Ornithimimidae,Tyrannosauridae))))) adds 53 Forcing abelisaurids to be tetanurines closer to birds than Torvosaurus (as in Forster, 1999) adds 55 steps. Noasaurids and Deltadreomeus clade with abelisaurids here. Forcing the Allosauria of Paul (Ornitholestes, Proceratosaurus, Allosaurus, carcharodontosaurids and tyrannosaurids) adds 56 more steps. Though constrained to be outside Paul's Allosauria, Piatnitzkysaurus, spinosauroids, Monolophosaurus and sinraptorids end up forming successively closer outgroups to it. Paul's ornitholestiines end up closer to tyrannosaurids than to allosaurids, and include Dilong and Guanlong as well. Forcing abelisauroids to be torvosaurids within Tetanurae (as in Paul, 1988) adds 57 steps. Spinosaurids and Monolophosaurus join the torvosaur part of this clade, while elaphrosaurs hang back with Ceratosaurus. Forcing spinosaurids to be coelophysoids closest to dilophosaurs (as in Paul, 1988) adds 60 steps. Forcing a traditional Carnosauria of sinraptorids, Torvosaurus, spinosaurids, abelisaurids, eustreptospondylids, carcharodontosaurids, allosaurids and tyrannosaurids (as in Kurzanov, 1989) adds 82 steps. Unlike Kurzanov's topology, abelisaurids emerge as most basal, Spinosauroidea is intact, and sinraptorids are sister to allosaurids. Forcing paravians outside of Dinosauria (as Feduccia, Martin, etc. suggest) adds 87 steps. Even though I specified Allosaurus as a dinosaur, all coelurosaurs are more parsimoniously "birds" when this happens. Forcing spinosaurids and birds to be sister taxa (as in Elzanowski and Wellnhofer, 1992) adds 93 steps. The clade ends up in a very basal coelurosaur position (ignoring for the moment that birds aren't with the rest of what's normally Paraves). Forcing Huene's original Carnosauria-Coelurosauria phylogeny of 1923, where coelophysids, ornithomimids, tyrannosaurids and Ceratosaurus are coelurosaurs, while Allosaurus and spinosauroids are carnosaurs adds 97 steps. Forcing Torvosaurus and Poekilopleuron to be more closely related to Plateosaurus than to coelophysoids and coelurosaurs (as in Galton and Jensen, 1979) adds 101 steps. The rest of Spinosauroidea, as well as Ceratosauria and Carnosauria end up joining the two 'megalosaurs' to form a large-bodied theropod clade sister to Sauropodomorpha. Within Saurischia, coelophysoids are more closely related to this clade than coelurosaurs. Mickey Mortimer
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[SciPy-dev] Implementing a distance matrix between two sets of vectors concept David Cournapeau david@ar.media.kyoto-u.ac... Wed Jul 4 22:38:11 CDT 2007 Peter Skomoroch wrote: > You're right, I was thinking the sparse data structures would help > with storing the input vectors themselves during the computation > rather than the final matrix (which will need to be 1/2 M*N if the > distance is symmetric)...this comes up a lot in collaborative > filtering where the dimensionality of the vectors is high, but most of > the vector entries are missing. Ok, that this basically means supporting sparse input, right ? I have to say that I don't know anything about sparse implementations issues in numpy (or any other language for that matter). I guess that performances mainly depend on the flexibility between matrix representation and data storage. Are sparse arrays directly supported in numpy ? More information about the Scipy-dev mailing list
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Fairchilds, TX Science Tutor Find a Fairchilds, TX Science Tutor ...Usually when I tutor my focus has been in Science and Mathematics, but my minor in Creative Writing and passion for writing have also resulted in helping to proof read countless essays and papers. If there's a topic you're interested in but it isn't listed below contact me and there's a good cha... 29 Subjects: including biostatistics, physics, physical science, physiology ...I am on the President's Honor Roll and have a GPA of 3.73. I am graduating in May and pursuing a Masters degree. I have had three chemical engineering internships through which I have gained experiences in the field. 22 Subjects: including chemical engineering, physical science, physics, geometry ...I have also completed additional course work and independent study on learning differences such as ADD/ADHD. I've taught science in middle and elementary school throughout the Houston area. I've also presented hands on fun labs for school enrichment classes, summer camp and remedial work. 18 Subjects: including ACT Science, reading, physical science, ESL/ESOL ...A mastery of geometry is essential to understanding the next level of mathematics, and I have had many years of experience using and teaching geometry. This is the first named mathematics course and is very fundamental in almost every field of study. Without a strong mastery of prealgebra, every following math and science course will be very difficult. 5 Subjects: including chemistry, geometry, algebra 1, algebra 2 ...I later earned a Master's in biology and even worked as a microbiologist for three years. I took my passion for the sciences and combined it with my passion for helping youngsters succeed in the classroom. I have now been teaching biology and chemistry (mostly biology) for five years and have b... 2 Subjects: including biology, chemistry Related Fairchilds, TX Tutors Fairchilds, TX Accounting Tutors Fairchilds, TX ACT Tutors Fairchilds, TX Algebra Tutors Fairchilds, TX Algebra 2 Tutors Fairchilds, TX Calculus Tutors Fairchilds, TX Geometry Tutors Fairchilds, TX Math Tutors Fairchilds, TX Prealgebra Tutors Fairchilds, TX Precalculus Tutors Fairchilds, TX SAT Tutors Fairchilds, TX SAT Math Tutors Fairchilds, TX Science Tutors Fairchilds, TX Statistics Tutors Fairchilds, TX Trigonometry Tutors
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[Haskell-beginners] Re: [Haskell-cafe] try, seq, and IO Daniel Fischer daniel.is.fischer at web.de Fri Sep 17 09:18:21 EDT 2010 On Friday 17 September 2010 13:17:30, Jeroen van Maanen wrote: > What I don't understand is the difference between: > try $ return $ seq theCheckSum maybeUpdatedModel > or even > try $! return $! seq theCheckSum maybeUpdatedModel > and > try $ evaluate $ seq theCheckSum maybeUpdatedModel > How is it possible that the exception escapes the former two > expressions, but gets caught by the third try? > Cheers, Jeroen It's quite devilish :) Well, the first and the third are rather straightforward. Let's start with the third. What that does is, evaluate (seq theCheckSum maybeUpdatedModel) to WHNF, if that throws an exception (of appropriate type, here SomeException), return (Left exception) else return (Right result). To evaluate `seq theCheckSum maybeUpdatedModel' to WHNF, theCheckSum has to be evaluated to WHNF (hence completely, since it's an Integer or something like), which in turn requires the complete evaluation of maybeUpdatedModel. The last throws an exception, that gets caught and wrapped in try, as expected and desired. The first one is `try (return thunk)' where thunk is "if needed, calculate `seq theCheckSum maybeUpdatedModel'". The return succeeds immediately, try wraps it in a Right and returns (Right thunk), as expected but not desired. The exception is thrown when you demand the evaluation of the thunk, after try has been left. Too lazy. Now the second one. try $! return $! seq t m === let z = return $! seq t m in z `seq` try z === let z = let v = seq t m in v `seq` return v in z `seq` try z === let { v = seq t m; z = v `seq` return v } in z `seq` try z === let v = seq t m in (v `seq` return v) `seq` try (return v) === ((t `seq` m) `seq` (return (t `seq` m)) `seq` try (return (t `seq` m)) So before try is even called, t has to be evaluated to WHNF, which throws an exception. Since it's thrown before try has been entered, try can't catch it. Too strict. So, first gives an uncaught exception after try has been left, second gives an uncaught exception before try has been entered. How do we get the exception to be thrown inside the try? That's easy. We mustn't allow try to return an exception-throwing thunk, so we need (return $! seq t m). But we mustn't cause the exception before try has been entered, so we need try $ return $! seq theCheckSum maybeUpdatedModel More information about the Beginners mailing list
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