Two-port network

Last updated

A two-port network (a kind of four-terminal network or quadripole) is an electrical network (circuit) or device with two pairs of terminals to connect to external circuits. Two terminals constitute a port if the currents applied to them satisfy the essential requirement known as the port condition: the electric current entering one terminal must equal the current emerging from the other terminal on the same port. [1] [2] The ports constitute interfaces where the network connects to other networks, the points where signals are applied or outputs are taken. In a two-port network, often port 1 is considered the input port and port 2 is considered the output port.

An electrical network is an interconnection of electrical components or a model of such an interconnection, consisting of electrical elements. An electrical circuit is a network consisting of a closed loop, giving a return path for the current. Linear electrical networks, a special type consisting only of sources, linear lumped elements, and linear distributed elements, have the property that signals are linearly superimposable. They are thus more easily analyzed, using powerful frequency domain methods such as Laplace transforms, to determine DC response, AC response, and transient response.

In electrical circuit theory, a port is a pair of terminals connecting an electrical network or circuit to an external circuit, a point of entry or exit for electrical energy. A port consists of two nodes (terminals) connected to an outside circuit, that meets the port condition; the currents flowing into the two nodes must be equal and opposite.

An electric current is a flow of electric charge. In electric circuits this charge is often carried by electrons moving through a wire. It can also be carried by ions in an electrolyte, or by both ions and electrons such as in an ionized gas (plasma).

Contents

The two-port network model is used in mathematical circuit analysis techniques to isolate portions of larger circuits. A two-port network is regarded as a "black box" with its properties specified by a matrix of numbers. This allows the response of the network to signals applied to the ports to be calculated easily, without solving for all the internal voltages and currents in the network. It also allows similar circuits or devices to be compared easily. For example, transistors are often regarded as two-ports, characterized by their h-parameters (see below) which are listed by the manufacturer. Any linear circuit with four terminals can be regarded as a two-port network provided that it does not contain an independent source and satisfies the port conditions.

In science, computing, and engineering, a black box is a device, system or object which can be viewed in terms of its inputs and outputs, without any knowledge of its internal workings. Its implementation is "opaque" (black). Almost anything might be referred to as a black box: a transistor, an algorithm, or the human brain.

In mathematics, a matrix is a rectangular array of numbers, symbols, or expressions, arranged in rows and columns. For example, the dimensions of the matrix below are 2 × 3, because there are two rows and three columns:

A linear circuit is an electronic circuit in which, for a sinusoidal input voltage of frequency f, any steady-state output of the circuit is also sinusoidal with frequency f. Note that the output need not be in phase with the input.

Examples of circuits analyzed as two-ports are filters, matching networks, transmission lines, transformers, and small-signal models for transistors (such as the hybrid-pi model). The analysis of passive two-port networks is an outgrowth of reciprocity theorems first derived by Lorentz. [3]

In signal processing, a filter is a device or process that removes some unwanted components or features from a signal. Filtering is a class of signal processing, the defining feature of filters being the complete or partial suppression of some aspect of the signal. Most often, this means removing some frequencies or frequency bands. However, filters do not exclusively act in the frequency domain; especially in the field of image processing many other targets for filtering exist. Correlations can be removed for certain frequency components and not for others without having to act in the frequency domain. Filters are widely used in electronics and telecommunication, in radio, television, audio recording, radar, control systems, music synthesis, image processing, and computer graphics.

In radio-frequency engineering, a transmission line is a specialized cable or other structure designed to conduct alternating current of radio frequency, that is, currents with a frequency high enough that their wave nature must be taken into account. Transmission lines are used for purposes such as connecting radio transmitters and receivers with their antennas, distributing cable television signals, trunklines routing calls between telephone switching centres, computer network connections and high speed computer data buses.

A transformer is a static electrical device that transfers electrical energy between two or more circuits. A varying current in one coil of the transformer produces a varying magnetic flux, which, in turn, induces a varying electromotive force across a second coil wound around the same core. Electrical energy can be transferred between the two coils, without a metallic connection between the two circuits. Faraday's law of induction discovered in 1831 described the induced voltage effect in any coil due to changing magnetic flux encircled by the coil.

In two-port mathematical models, the network is described by a 2 by 2 square matrix of complex numbers. The common models that are used are referred to as z-parameters, y-parameters, h-parameters, g-parameters, and ABCD-parameters, each described individually below. These are all limited to linear networks since an underlying assumption of their derivation is that any given circuit condition is a linear superposition of various short-circuit and open circuit conditions. They are usually expressed in matrix notation, and they establish relations between the variables

A complex number is a number that can be expressed in the form a + bi, where a and b are real numbers, and i is a solution of the equation x2 = −1. Because no real number satisfies this equation, i is called an imaginary number. For the complex number a + bi, a is called the real part, and b is called the imaginary part. Despite the historical nomenclature "imaginary", complex numbers are regarded in the mathematical sciences as just as "real" as the real numbers, and are fundamental in many aspects of the scientific description of the natural world.

${\displaystyle V_{1}}$, voltage across port 1
${\displaystyle I_{1}}$, current into port 1
${\displaystyle V_{2}}$, voltage across port 2
${\displaystyle I_{2}}$, current into port 2

which are shown in figure 1. The difference between the various models lies in which of these variables are regarded as the independent variables. These current and voltage variables are most useful at low-to-moderate frequencies. At high frequencies (e.g., microwave frequencies), the use of power and energy variables is more appropriate, and the two-port currentvoltage approach is replaced by an approach based upon scattering parameters.

Voltage, electric potential difference, electric pressure or electric tension is the difference in electric potential between two points. The difference in electric potential between two points in a static electric field is defined as the work needed per unit of charge to move a test charge between the two points. In the International System of Units, the derived unit for voltage is named volt. In SI units, work per unit charge is expressed as joules per coulomb, where 1 volt = 1 joule per 1 coulomb. The official SI definition for volt uses power and current, where 1 volt = 1 watt per 1 ampere. This definition is equivalent to the more commonly used 'joules per coulomb'. Voltage or electric potential difference is denoted symbolically by V, but more often simply as V, for instance in the context of Ohm's or Kirchhoff's circuit laws.

In physics, power is the rate of doing work or of transferring heat, i.e. the amount of energy transferred or converted per unit time. Having no direction, it is a scalar quantity. In the International System of Units, the unit of power is the joule per second (J/s), known as the watt in honour of James Watt, the eighteenth-century developer of the condenser steam engine. Another common and traditional measure is horsepower. Being the rate of work, the equation for power can be written:

In physics, energy is the quantitative property that must be transferred to an object in order to perform work on, or to heat, the object. Energy is a conserved quantity; the law of conservation of energy states that energy can be converted in form, but not created or destroyed. The SI unit of energy is the joule, which is the energy transferred to an object by the work of moving it a distance of 1 metre against a force of 1 newton.

General properties

There are certain properties of two-ports that frequently occur in practical networks and can be used to greatly simplify the analysis. These include:

Reciprocal networks
A network is said to be reciprocal if the voltage appearing at port 2 due to a current applied at port 1 is the same as the voltage appearing at port 1 when the same current is applied to port 2. Exchanging voltage and current results in an equivalent definition of reciprocity. A network that consists entirely of linear passive components (that is, resistors, capacitors and inductors) is usually reciprocal, a notable exception being passive circulators and isolators that contain magnetized materials. In general, it will not be reciprocal if it contains active components such as generators or transistors. [4]
Symmetrical networks
A network is symmetrical if its input impedance is equal to its output impedance. Most often, but not necessarily, symmetrical networks are also physically symmetrical. Sometimes also antimetrical networks are of interest. These are networks where the input and output impedances are the duals of each other. [5]
Lossless network
A lossless network is one which contains no resistors or other dissipative elements. [6]

Impedance parameters (z-parameters)

${\displaystyle {\begin{bmatrix}V_{1}\\V_{2}\end{bmatrix}}={\begin{bmatrix}z_{11}&z_{12}\\z_{21}&z_{22}\end{bmatrix}}{\begin{bmatrix}I_{1}\\I_{2}\end{bmatrix}}}$

where

{\displaystyle {\begin{aligned}z_{11}\,&{\stackrel {\text{def}}{=}}\,\left.{\frac {V_{1}}{I_{1}}}\right|_{I_{2}=0}\qquad z_{12}\,{\stackrel {\text{def}}{=}}\,\left.{\frac {V_{1}}{I_{2}}}\right|_{I_{1}=0}\\z_{21}\,&{\stackrel {\text{def}}{=}}\,\left.{\frac {V_{2}}{I_{1}}}\right|_{I_{2}=0}\qquad z_{22}\,{\stackrel {\text{def}}{=}}\,\left.{\frac {V_{2}}{I_{2}}}\right|_{I_{1}=0}\end{aligned}}}

All the z-parameters have dimensions of ohms.

For reciprocal networks ${\displaystyle \textstyle z_{12}=z_{21}}$. For symmetrical networks ${\displaystyle \textstyle z_{11}=z_{22}}$. For reciprocal lossless networks all the ${\displaystyle \textstyle z_{\mathrm {mn} }}$ are purely imaginary. [7]

Example: bipolar current mirror with emitter degeneration

Figure 3 shows a bipolar current mirror with emitter resistors to increase its output resistance. [nb 1] Transistor Q1 is diode connected, which is to say its collector-base voltage is zero. Figure 4 shows the small-signal circuit equivalent to Figure 3. Transistor Q1 is represented by its emitter resistance rEVT / IE (VT = thermal voltage, IE = Q-point emitter current), a simplification made possible because the dependent current source in the hybrid-pi model for Q1 draws the same current as a resistor 1 / gm connected across rπ. The second transistor Q2 is represented by its hybrid-pi model. Table 1 below shows the z-parameter expressions that make the z-equivalent circuit of Figure 2 electrically equivalent to the small-signal circuit of Figure 4.

Table 1
ExpressionApproximation
${\displaystyle R_{21}=\left.{\frac {V_{2}}{I_{1}}}\right|_{I_{2}=0}}$${\displaystyle -(\beta r_{O}-R_{E}){\frac {r_{E}+R_{E}}{r_{\pi }+r_{E}+2R_{E}}}}$${\displaystyle -\beta r_{o}{\frac {r_{E}+R_{E}}{r_{\pi }+2R_{E}}}}$
${\displaystyle R_{11}=\left.{\frac {V_{1}}{I_{1}}}\right|_{I_{2}=0}}$${\displaystyle (r_{E}+R_{E})\|(r_{\pi }+R_{E})}$ [nb 2]
${\displaystyle R_{22}=\left.{\frac {V_{2}}{I_{2}}}\right|_{I_{1}=0}}$ ${\displaystyle \left(1+\beta {\frac {R_{E}}{r_{\pi }+r_{E}+2R_{E}}}\right)r_{O}+{\frac {r_{\pi }+r_{E}+R_{E}}{r_{\pi }+r_{E}+2R_{E}}}R_{E}}$  ${\displaystyle \left(1+\beta {\frac {R_{E}}{r_{\pi }+2R_{E}}}\right)r_{O}}$
${\displaystyle R_{12}=\left.{\frac {V_{1}}{I_{2}}}\right|_{I_{1}=0}}$${\displaystyle R_{E}{\frac {r_{E}+R_{E}}{r_{\pi }+r_{E}+2R_{E}}}}$${\displaystyle R_{E}{\frac {r_{E}+R_{E}}{r_{\pi }+2R_{E}}}}$

The negative feedback introduced by resistors RE can be seen in these parameters. For example, when used as an active load in a differential amplifier, I1 ≈ −I2, making the output impedance of the mirror approximately R22 -R21 ≈ 2 β rORE /(rπ + 2RE) compared to only rO without feedback (that is with RE = 0 Ω) . At the same time, the impedance on the reference side of the mirror is approximately R11  R12${\displaystyle {\frac {r_{\pi }}{r_{\pi }+2R_{E}}}}$${\displaystyle (r_{E}+R_{E})}$, only a moderate value, but still larger than rE with no feedback. In the differential amplifier application, a large output resistance increases the difference-mode gain, a good thing, and a small mirror input resistance is desirable to avoid Miller effect.

${\displaystyle {\begin{bmatrix}I_{1}\\I_{2}\end{bmatrix}}={\begin{bmatrix}y_{11}&y_{12}\\y_{21}&y_{22}\end{bmatrix}}{\begin{bmatrix}V_{1}\\V_{2}\end{bmatrix}}}$

where

{\displaystyle {\begin{aligned}y_{11}\,&{\stackrel {\text{def}}{=}}\,\left.{\frac {I_{1}}{V_{1}}}\right|_{V_{2}=0}\qquad y_{12}\,{\stackrel {\text{def}}{=}}\,\left.{\frac {I_{1}}{V_{2}}}\right|_{V_{1}=0}\\y_{21}\,&{\stackrel {\text{def}}{=}}\,\left.{\frac {I_{2}}{V_{1}}}\right|_{V_{2}=0}\qquad y_{22}\,{\stackrel {\text{def}}{=}}\,\left.{\frac {I_{2}}{V_{2}}}\right|_{V_{1}=0}\end{aligned}}}

All the Y-parameters have dimensions of siemens.

For reciprocal networks ${\displaystyle \textstyle y_{12}=y_{21}}$. For symmetrical networks ${\displaystyle \textstyle y_{11}=y_{22}}$. For reciprocal lossless networks all the ${\displaystyle \textstyle y_{\mathrm {mn} }}$ are purely imaginary. [7]

Hybrid parameters (h-parameters)

${\displaystyle {\begin{bmatrix}V_{1}\\I_{2}\end{bmatrix}}={\begin{bmatrix}h_{11}&h_{12}\\h_{21}&h_{22}\end{bmatrix}}{\begin{bmatrix}I_{1}\\V_{2}\end{bmatrix}}}$

where

{\displaystyle {\begin{aligned}h_{11}\,&{\stackrel {\text{def}}{=}}\,\left.{\frac {V_{1}}{I_{1}}}\right|_{V_{2}=0}\qquad h_{12}\,{\stackrel {\text{def}}{=}}\,\left.{\frac {V_{1}}{V_{2}}}\right|_{I_{1}=0}\\h_{21}\,&{\stackrel {\text{def}}{=}}\,\left.{\frac {I_{2}}{I_{1}}}\right|_{V_{2}=0}\qquad h_{22}\,{\stackrel {\text{def}}{=}}\,\left.{\frac {I_{2}}{V_{2}}}\right|_{I_{1}=0}\end{aligned}}}

This circuit is often selected when a current amplifier is desired at the output. The resistors shown in the diagram can be general impedances instead.

Off-diagonal h-parameters are dimensionless, while diagonal members have dimensions the reciprocal of one another.

Example: common-base amplifier

Note: Tabulated formulas in Table 2 make the h-equivalent circuit of the transistor from Figure 6 agree with its small-signal low-frequency hybrid-pi model in Figure 7. Notation: rπ = base resistance of transistor, rO = output resistance, and gm = transconductance. The negative sign for h21 reflects the convention that I1, I2 are positive when directed into the two-port. A non-zero value for h12 means the output voltage affects the input voltage, that is, this amplifier is bilateral. If h12 = 0, the amplifier is unilateral.

Table 2
ExpressionApproximation
${\displaystyle h_{21}=\left.{\frac {I_{2}}{I_{1}}}\right|_{V_{2}=0}}$${\displaystyle -{\frac {{\frac {\beta }{\beta +1}}r_{O}+r_{\pi }}{r_{O}+r_{\pi }}}}$${\displaystyle -{\frac {\beta }{\beta +1}}}$
${\displaystyle h_{11}=\left.{\frac {V_{1}}{I_{1}}}\right|_{V_{2}=0}}$${\displaystyle r_{\pi }\|r_{O}}$${\displaystyle r_{\pi }}$
${\displaystyle h_{22}=\left.{\frac {I_{2}}{V_{2}}}\right|_{I_{1}=0}}$${\displaystyle {\frac {1}{(\beta +1)(r_{O}+r_{\pi })}}}$${\displaystyle {\frac {1}{(\beta +1)r_{O}}}}$
${\displaystyle h_{12}=\left.{\frac {V_{1}}{V_{2}}}\right|_{I_{1}=0}}$${\displaystyle {\frac {r_{\pi }}{r_{O}+r_{\pi }}}}$${\displaystyle {\frac {r_{\pi }}{r_{O}}}\ll 1}$

History

The h-parameters were initially called series-parallel parameters. The term hybrid to describe these parameters was coined by D. A. Alsberg in 1953 in "Transistor metrology". [8] In 1954 a joint committee of the IRE and the AIEE adopted the term h parameters and recommended that these become the standard method of testing and characterising transistors because they were "peculiarly adaptable to the physical characteristics of transistors". [9] In 1956 the recommendation became an issued standard; 56 IRE 28.S2. Following the merge of these two organisations as the IEEE, the standard became Std 218-1956 and was reaffirmed in 1980, but has now been withdrawn. [10]

Inverse hybrid parameters (g-parameters)

${\displaystyle {\begin{bmatrix}I_{1}\\V_{2}\end{bmatrix}}={\begin{bmatrix}g_{11}&g_{12}\\g_{21}&g_{22}\end{bmatrix}}{\begin{bmatrix}V_{1}\\I_{2}\end{bmatrix}}}$

where

{\displaystyle {\begin{aligned}g_{11}\,&{\stackrel {\text{def}}{=}}\,\left.{\frac {I_{1}}{V_{1}}}\right|_{I_{2}=0}\qquad g_{12}\,{\stackrel {\text{def}}{=}}\,\left.{\frac {I_{1}}{I_{2}}}\right|_{V_{1}=0}\\g_{21}\,&{\stackrel {\text{def}}{=}}\,\left.{\frac {V_{2}}{V_{1}}}\right|_{I_{2}=0}\qquad g_{22}\,{\stackrel {\text{def}}{=}}\,\left.{\frac {V_{2}}{I_{2}}}\right|_{V_{1}=0}\end{aligned}}}

Often this circuit is selected when a voltage amplifier is wanted at the output. Off-diagonal g-parameters are dimensionless, while diagonal members have dimensions the reciprocal of one another. The resistors shown in the diagram can be general impedances instead.

Example: common-base amplifier

Note: Tabulated formulas in Table 3 make the g-equivalent circuit of the transistor from Figure 8 agree with its small-signal low-frequency hybrid-pi model in Figure 9. Notation: rπ = base resistance of transistor, rO = output resistance, and gm = transconductance. The negative sign for g12 reflects the convention that I1, I2 are positive when directed into the two-port. A non-zero value for g12 means the output current affects the input current, that is, this amplifier is bilateral. If g12 = 0, the amplifier is unilateral.

Table 3
ExpressionApproximation
${\displaystyle g_{21}=\left.{\frac {V_{2}}{V_{1}}}\right|_{I_{2}=0}}$${\displaystyle {\frac {r_{o}}{r_{\pi }}}+g_{m}r_{O}+1}$${\displaystyle g_{m}r_{O}}$
${\displaystyle g_{11}=\left.{\frac {I_{1}}{V_{1}}}\right|_{I_{2}=0}}$${\displaystyle {\frac {1}{r_{\pi }}}}$${\displaystyle {\frac {1}{r_{\pi }}}}$
${\displaystyle g_{22}=\left.{\frac {V_{2}}{I_{2}}}\right|_{V_{1}=0}}$${\displaystyle r_{O}}$${\displaystyle r_{O}}$
${\displaystyle g_{12}=\left.{\frac {I_{1}}{I_{2}}}\right|_{V_{1}=0}}$${\displaystyle -{\frac {\beta +1}{\beta }}}$${\displaystyle -1}$

ABCD-parameters

The ABCD-parameters are known variously as chain, cascade, or transmission parameters. There are a number of definitions given for ABCD parameters, the most common is, [11] [12]

${\displaystyle {\begin{bmatrix}V_{1}\\I_{1}\end{bmatrix}}={\begin{bmatrix}A&B\\C&D\end{bmatrix}}{\begin{bmatrix}V_{2}\\-I_{2}\end{bmatrix}}}$

For reciprocal networks ${\displaystyle \scriptstyle AD-BC=1}$. For symmetrical networks ${\displaystyle \scriptstyle A=D}$. For networks which are reciprocal and lossless, A and D are purely real while B and C are purely imaginary. [6]

This representation is preferred because when the parameters are used to represent a cascade of two-ports, the matrices are written in the same order that a network diagram would be drawn, that is, left to right. However, a variant definition is also in use,

${\displaystyle {\begin{bmatrix}V_{2}\\-I_{2}\end{bmatrix}}={\begin{bmatrix}A'&B'\\C'&D'\end{bmatrix}}{\begin{bmatrix}V_{1}\\I_{1}\end{bmatrix}}}$

where

{\displaystyle {\begin{aligned}A'\,&{\stackrel {\text{def}}{=}}\,\left.{\frac {V_{2}}{V_{1}}}\right|_{I_{1}=0}&\qquad B'\,&{\stackrel {\text{def}}{=}}\,\left.{\frac {V_{2}}{I_{1}}}\right|_{V_{1}=0}\\C'\,&{\stackrel {\text{def}}{=}}\,\left.-{\frac {I_{2}}{V_{1}}}\right|_{I_{1}=0}&\qquad D'\,&{\stackrel {\text{def}}{=}}\,\left.-{\frac {I_{2}}{I_{1}}}\right|_{V_{1}=0}\end{aligned}}}

The negative sign of ${\displaystyle \scriptstyle -I_{2}}$ arises to make the output current of one cascaded stage (as it appears in the matrix) equal to the input current of the next. Without the minus sign the two currents would have opposite senses because the positive direction of current, by convention, is taken as the current entering the port. Consequently, the input voltage/current matrix vector can be directly replaced with the matrix equation of the preceding cascaded stage to form a combined ${\displaystyle \scriptstyle A'B'C'D'}$ matrix.

The terminology of representing the ${\displaystyle \scriptstyle ABCD}$ parameters as a matrix of elements designated a11 etc. as adopted by some authors [13] and the inverse ${\displaystyle \scriptstyle A'B'C'D'}$ parameters as a matrix of elements designated b11 etc. is used here for both brevity and to avoid confusion with circuit elements.

{\displaystyle {\begin{aligned}\left\lbrack \mathbf {a} \right\rbrack &={\begin{bmatrix}a_{11}&a_{12}\\a_{21}&a_{22}\end{bmatrix}}={\begin{bmatrix}A&B\\C&D\end{bmatrix}}\\\left\lbrack \mathbf {b} \right\rbrack &={\begin{bmatrix}b_{11}&b_{12}\\b_{21}&b_{22}\end{bmatrix}}={\begin{bmatrix}A'&B'\\C'&D'\end{bmatrix}}\end{aligned}}}

An ABCD matrix has been defined for Telephony four-wire Transmission Systems by P K Webb in British Post Office Research Department Report 630 in 1977.

Table of transmission parameters

The table below lists ABCD and inverse ABCD parameters for some simple network elements.

Element[a] matrix[b] matrixRemarks
Series impedance${\displaystyle {\begin{bmatrix}1&Z\\0&1\end{bmatrix}}}$${\displaystyle {\begin{bmatrix}1&-Z\\0&1\end{bmatrix}}}$Z, impedance
Shunt admittance${\displaystyle {\begin{bmatrix}1&0\\Y&1\end{bmatrix}}}$${\displaystyle {\begin{bmatrix}1&0\\-Y&1\end{bmatrix}}}$Y, admittance
Series inductor${\displaystyle {\begin{bmatrix}1&sL\\0&1\end{bmatrix}}}$${\displaystyle {\begin{bmatrix}1&-sL\\0&1\end{bmatrix}}}$L, inductance
s, complex angular frequency
Shunt inductor${\displaystyle {\begin{bmatrix}1&0\\{1 \over sL}&1\end{bmatrix}}}$${\displaystyle {\begin{bmatrix}1&0\\-{\frac {1}{sL}}&1\end{bmatrix}}}$L, inductance
s, complex angular frequency
Series capacitor${\displaystyle {\begin{bmatrix}1&{1 \over sC}\\0&1\end{bmatrix}}}$${\displaystyle {\begin{bmatrix}1&-{\frac {1}{sC}}\\0&1\end{bmatrix}}}$C, capacitance
s, complex angular frequency
Shunt capacitor${\displaystyle {\begin{bmatrix}1&0\\sC&1\end{bmatrix}}}$${\displaystyle {\begin{bmatrix}1&0\\-sC&1\end{bmatrix}}}$C, capacitance
s, complex angular frequency
Transmission line${\displaystyle {\begin{bmatrix}\cosh \left(\gamma l\right)&Z_{0}\sinh \left(\gamma l\right)\\{\frac {1}{Z_{0}}}\sinh \left(\gamma l\right)&\cosh \left(\gamma l\right)\end{bmatrix}}}$${\displaystyle {\begin{bmatrix}\cosh \left(\gamma l\right)&-Z_{0}\sinh \left(\gamma l\right)\\-{\frac {1}{Z_{0}}}\sinh \left(\gamma l\right)&\cosh \left(\gamma l\right)\end{bmatrix}}}$ [14] Z0, characteristic impedance
γ, propagation constant (${\displaystyle \gamma =\alpha +i\beta }$)
l, length of transmission line (m)

Scattering parameters (S-parameters)

The previous parameters are all defined in terms of voltages and currents at ports. S-parameters are different, and are defined in terms of incident and reflected waves at ports. S-parameters are used primarily at UHF and microwave frequencies where it becomes difficult to measure voltages and currents directly. On the other hand, incident and reflected power are easy to measure using directional couplers. The definition is, [15]

${\displaystyle {\begin{bmatrix}b_{1}\\b_{2}\end{bmatrix}}={\begin{bmatrix}S_{11}&S_{12}\\S_{21}&S_{22}\end{bmatrix}}{\begin{bmatrix}a_{1}\\a_{2}\end{bmatrix}}}$

where the ${\displaystyle \scriptstyle a_{k}}$ are the incident waves and the ${\displaystyle \scriptstyle b_{k}}$ are the reflected waves at port k. It is conventional to define the ${\displaystyle \scriptstyle a_{k}}$ and ${\displaystyle \scriptstyle b_{k}}$ in terms of the square root of power. Consequently, there is a relationship with the wave voltages (see main article for details). [16]

For reciprocal networks ${\displaystyle \textstyle S_{12}=S_{21}}$. For symmetrical networks ${\displaystyle \textstyle S_{11}=S_{22}}$. For antimetrical networks ${\displaystyle \textstyle S_{11}=-S_{22}}$. [17] For lossless reciprocal networks ${\displaystyle \textstyle |S_{11}|=|S_{22}|}$ and ${\displaystyle \textstyle |S_{11}|^{2}+|S_{12}|^{2}=1}$. [18]

Scattering transfer parameters (T-parameters)

Scattering transfer parameters, like scattering parameters, are defined in terms of incident and reflected waves. The difference is that T-parameters relate the waves at port 1 to the waves at port 2 whereas S-parameters relate the reflected waves to the incident waves. In this respect T-parameters fill the same role as ABCD parameters and allow the T-parameters of cascaded networks to be calculated by matrix multiplication of the component networks. T-parameters, like ABCD parameters, can also be called transmission parameters. The definition is, [15] [19]

${\displaystyle {\begin{bmatrix}a_{1}\\b_{1}\end{bmatrix}}={\begin{bmatrix}T_{11}&T_{12}\\T_{21}&T_{22}\end{bmatrix}}{\begin{bmatrix}b_{2}\\a_{2}\end{bmatrix}}}$

T-parameters are not so easy to measure directly unlike S-parameters. However, S-parameters are easily converted to T-parameters, see main article for details. [20]

Combinations of two-port networks

When two or more two-port networks are connected, the two-port parameters of the combined network can be found by performing matrix algebra on the matrices of parameters for the component two-ports. The matrix operation can be made particularly simple with an appropriate choice of two-port parameters to match the form of connection of the two-ports. For instance, the z-parameters are best for series connected ports.

The combination rules need to be applied with care. Some connections (when dissimilar potentials are joined) result in the port condition being invalidated and the combination rule will no longer apply. A Brune test can be used to check the permissibility of the combination. This difficulty can be overcome by placing 1:1 ideal transformers on the outputs of the problem two-ports. This does not change the parameters of the two-ports, but does ensure that they will continue to meet the port condition when interconnected. An example of this problem is shown for series-series connections in figures 11 and 12 below. [21]

Series-series connection

When two-ports are connected in a series-series configuration as shown in figure 10, the best choice of two-port parameter is the z-parameters. The z-parameters of the combined network are found by matrix addition of the two individual z-parameter matrices. [22] [23]

${\displaystyle \lbrack \mathbf {z} \rbrack =\lbrack \mathbf {z} \rbrack _{1}+\lbrack \mathbf {z} \rbrack _{2}}$

As mentioned above, there are some networks which will not yield directly to this analysis. [21] A simple example is a two-port consisting of a L-network of resistors R1 and R2. The z-parameters for this network are;

${\displaystyle \lbrack \mathbf {z} \rbrack _{1}={\begin{bmatrix}R_{1}+R_{2}&R_{2}\\R_{2}&R_{2}\end{bmatrix}}}$

Figure 11 shows two identical such networks connected in series-series. The total z-parameters predicted by matrix addition are;

${\displaystyle \lbrack \mathbf {z} \rbrack =\lbrack \mathbf {z} \rbrack _{1}+\lbrack \mathbf {z} \rbrack _{2}=2\lbrack \mathbf {z} \rbrack _{1}={\begin{bmatrix}2R_{1}+2R_{2}&2R_{2}\\2R_{2}&2R_{2}\end{bmatrix}}}$

However, direct analysis of the combined circuit shows that,

${\displaystyle \lbrack \mathbf {z} \rbrack ={\begin{bmatrix}R_{1}+2R_{2}&2R_{2}\\2R_{2}&2R_{2}\end{bmatrix}}}$

The discrepancy is explained by observing that R1 of the lower two-port has been by-passed by the short-circuit between two terminals of the output ports. This results in no current flowing through one terminal in each of the input ports of the two individual networks. Consequently, the port condition is broken for both the input ports of the original networks since current is still able to flow into the other terminal. This problem can be resolved by inserting an ideal transformer in the output port of at least one of the two-port networks. While this is a common text-book approach to presenting the theory of two-ports, the practicality of using transformers is a matter to be decided for each individual design.

Parallel-parallel connection

When two-ports are connected in a parallel-parallel configuration as shown in figure 13, the best choice of two-port parameter is the y-parameters. The y-parameters of the combined network are found by matrix addition of the two individual y-parameter matrices. [24]

${\displaystyle \lbrack \mathbf {y} \rbrack =\lbrack \mathbf {y} \rbrack _{1}+\lbrack \mathbf {y} \rbrack _{2}}$

Series-parallel connection

When two-ports are connected in a series-parallel configuration as shown in figure 14, the best choice of two-port parameter is the h-parameters. The h-parameters of the combined network are found by matrix addition of the two individual h-parameter matrices. [25]

${\displaystyle \lbrack \mathbf {h} \rbrack =\lbrack \mathbf {h} \rbrack _{1}+\lbrack \mathbf {h} \rbrack _{2}}$

Parallel-series connection

When two-ports are connected in a parallel-series configuration as shown in figure 15, the best choice of two-port parameter is the g-parameters. The g-parameters of the combined network are found by matrix addition of the two individual g-parameter matrices.

${\displaystyle \lbrack \mathbf {g} \rbrack =\lbrack \mathbf {g} \rbrack _{1}+\lbrack \mathbf {g} \rbrack _{2}}$

When two-ports are connected with the output port of the first connected to the input port of the second (a cascade connection) as shown in figure 16, the best choice of two-port parameter is the ABCD-parameters. The a-parameters of the combined network are found by matrix multiplication of the two individual a-parameter matrices. [26]

${\displaystyle \lbrack \mathbf {a} \rbrack =\lbrack \mathbf {a} \rbrack _{1}\cdot \lbrack \mathbf {a} \rbrack _{2}}$

A chain of n two-ports may be combined by matrix multiplication of the n matrices. To combine a cascade of b-parameter matrices, they are again multiplied, but the multiplication must be carried out in reverse order, so that;

${\displaystyle \lbrack \mathbf {b} \rbrack =\lbrack \mathbf {b} \rbrack _{2}\cdot \lbrack \mathbf {b} \rbrack _{1}}$

Example

Suppose we have a two-port network consisting of a series resistor R followed by a shunt capacitor C. We can model the entire network as a cascade of two simpler networks:

{\displaystyle {\begin{aligned}[]\left\lbrack \mathbf {b} \right\rbrack _{1}&={\begin{bmatrix}1&-R\\0&1\end{bmatrix}}\\\left\lbrack \mathbf {b} \right\rbrack _{2}&={\begin{bmatrix}1&0\\-sC&1\end{bmatrix}}\end{aligned}}}

The transmission matrix for the entire network ${\displaystyle \scriptstyle \lbrack \mathbf {b} \rbrack }$ is simply the matrix multiplication of the transmission matrices for the two network elements:

{\displaystyle {\begin{aligned}[]\lbrack \mathbf {b} \rbrack &=\lbrack \mathbf {b} \rbrack _{2}\cdot \lbrack \mathbf {b} \rbrack _{1}\\&={\begin{bmatrix}1&0\\-sC&1\end{bmatrix}}{\begin{bmatrix}1&-R\\0&1\end{bmatrix}}\\&={\begin{bmatrix}1&-R\\-sC&1+sCR\end{bmatrix}}\end{aligned}}}

Thus:

${\displaystyle {\begin{bmatrix}V_{2}\\-I_{2}\end{bmatrix}}={\begin{bmatrix}1&-R\\-sC&1+sCR\end{bmatrix}}{\begin{bmatrix}V_{1}\\I_{1}\end{bmatrix}}}$

Interrelation of parameters

${\displaystyle \mathbf {[z]} }$${\displaystyle \mathbf {[y]} }$${\displaystyle \mathbf {[h]} }$${\displaystyle \mathbf {[g]} }$${\displaystyle \mathbf {[a]} }$${\displaystyle \mathbf {[b]} }$
${\displaystyle \mathbf {[z]} }$${\displaystyle {\begin{bmatrix}z_{11}&z_{12}\\z_{21}&z_{22}\end{bmatrix}}}$${\displaystyle {\frac {1}{\Delta \mathbf {[y]} }}{\begin{bmatrix}y_{22}&-y_{12}\\-y_{21}&y_{11}\end{bmatrix}}}$${\displaystyle {\frac {1}{h_{22}}}{\begin{bmatrix}\Delta \mathbf {[h]} &h_{12}\\-h_{21}&1\end{bmatrix}}}$${\displaystyle {\frac {1}{g_{11}}}{\begin{bmatrix}1&-g_{12}\\g_{21}&\Delta \mathbf {[g]} \end{bmatrix}}}$${\displaystyle {\frac {1}{a_{21}}}{\begin{bmatrix}a_{11}&\Delta \mathbf {[a]} \\1&a_{22}\end{bmatrix}}}$${\displaystyle {\frac {1}{b_{21}}}{\begin{bmatrix}-b_{22}&-1\\-\Delta \mathbf {[b]} &-b_{11}\end{bmatrix}}}$
${\displaystyle \mathbf {[y]} }$${\displaystyle {\frac {1}{\Delta \mathbf {[z]} }}{\begin{bmatrix}z_{22}&-z_{12}\\-z_{21}&z_{11}\end{bmatrix}}}$${\displaystyle {\begin{bmatrix}y_{11}&y_{12}\\y_{21}&y_{22}\end{bmatrix}}}$${\displaystyle {\frac {1}{h_{11}}}{\begin{bmatrix}1&-h_{12}\\h_{21}&\Delta \mathbf {[h]} \end{bmatrix}}}$${\displaystyle {\frac {1}{g_{22}}}{\begin{bmatrix}\Delta \mathbf {[g]} &g_{12}\\-g_{21}&1\end{bmatrix}}}$${\displaystyle {\frac {1}{a_{12}}}{\begin{bmatrix}a_{22}&-\Delta \mathbf {[a]} \\-1&a_{11}\end{bmatrix}}}$${\displaystyle {\frac {1}{b_{12}}}{\begin{bmatrix}-b_{11}&1\\\Delta \mathbf {[b]} &-b_{22}\end{bmatrix}}}$
${\displaystyle \mathbf {[h]} }$${\displaystyle {\frac {1}{z_{22}}}{\begin{bmatrix}\Delta \mathbf {[z]} &z_{12}\\-z_{21}&1\end{bmatrix}}}$${\displaystyle {\frac {1}{y_{11}}}{\begin{bmatrix}1&-y_{12}\\y_{21}&\Delta \mathbf {[y]} \end{bmatrix}}}$${\displaystyle {\begin{bmatrix}h_{11}&h_{12}\\h_{21}&h_{22}\end{bmatrix}}}$${\displaystyle {\frac {1}{\Delta \mathbf {[g]} }}{\begin{bmatrix}g_{22}&-g_{12}\\-g_{21}&g_{11}\end{bmatrix}}}$${\displaystyle {\frac {1}{a_{22}}}{\begin{bmatrix}a_{12}&\Delta \mathbf {[a]} \\-1&a_{21}\end{bmatrix}}}$${\displaystyle {\frac {1}{b_{11}}}{\begin{bmatrix}-b_{12}&1\\-\Delta \mathbf {[b]} &-b_{21}\end{bmatrix}}}$
${\displaystyle \mathbf {[g]} }$${\displaystyle {\frac {1}{z_{11}}}{\begin{bmatrix}1&-z_{12}\\z_{21}&\Delta \mathbf {[z]} \end{bmatrix}}}$${\displaystyle {\frac {1}{y_{22}}}{\begin{bmatrix}\Delta \mathbf {[y]} &y_{12}\\-y_{21}&1\end{bmatrix}}}$${\displaystyle {\frac {1}{\Delta \mathbf {[h]} }}{\begin{bmatrix}h_{22}&-h_{12}\\-h_{21}&h_{11}\end{bmatrix}}}$${\displaystyle {\begin{bmatrix}g_{11}&g_{12}\\g_{21}&g_{22}\end{bmatrix}}}$${\displaystyle {\frac {1}{a_{11}}}{\begin{bmatrix}a_{21}&-\Delta \mathbf {[a]} \\1&a_{12}\end{bmatrix}}}$${\displaystyle {\frac {1}{b_{22}}}{\begin{bmatrix}-b_{21}&-1\\\Delta \mathbf {[b]} &-b_{12}\end{bmatrix}}}$
${\displaystyle \mathbf {[a]} }$${\displaystyle {\frac {1}{z_{21}}}{\begin{bmatrix}z_{11}&\Delta \mathbf {[z]} \\1&z_{22}\end{bmatrix}}}$${\displaystyle {\frac {1}{y_{21}}}{\begin{bmatrix}-y_{22}&-1\\-\Delta \mathbf {[y]} &-y_{11}\end{bmatrix}}}$${\displaystyle {\frac {1}{h_{21}}}{\begin{bmatrix}-\Delta \mathbf {[h]} &-h_{11}\\-h_{22}&-1\end{bmatrix}}}$${\displaystyle {\frac {1}{g_{21}}}{\begin{bmatrix}1&g_{22}\\g_{11}&\Delta \mathbf {[g]} \end{bmatrix}}}$${\displaystyle {\begin{bmatrix}a_{11}&a_{12}\\a_{21}&a_{22}\end{bmatrix}}}$${\displaystyle {\frac {1}{\Delta \mathbf {[b]} }}{\begin{bmatrix}b_{22}&-b_{12}\\-b_{21}&b_{11}\end{bmatrix}}}$
${\displaystyle \mathbf {[b]} }$${\displaystyle {\frac {1}{z_{12}}}{\begin{bmatrix}z_{22}&-\Delta \mathbf {[z]} \\-1&z_{11}\end{bmatrix}}}$${\displaystyle {\frac {1}{y_{12}}}{\begin{bmatrix}-y_{11}&1\\\Delta \mathbf {[y]} &-y_{22}\end{bmatrix}}}$${\displaystyle {\frac {1}{h_{12}}}{\begin{bmatrix}1&-h_{11}\\-h_{22}&\Delta \mathbf {[h]} \end{bmatrix}}}$${\displaystyle {\frac {1}{g_{12}}}{\begin{bmatrix}-\Delta \mathbf {[g]} &g_{22}\\g_{11}&-1\end{bmatrix}}}$${\displaystyle {\frac {1}{\Delta \mathbf {[a]} }}{\begin{bmatrix}a_{22}&-a_{12}\\-a_{21}&a_{11}\end{bmatrix}}}$${\displaystyle {\begin{bmatrix}b_{11}&b_{12}\\b_{21}&b_{22}\end{bmatrix}}}$

Where ${\displaystyle \Delta \mathbf {[x]} }$ is the determinant of [x].

Certain pairs of matrices have a particularly simple relationship. The admittance parameters are the matrix inverse of the impedance parameters, the inverse hybrid parameters are the matrix inverse of the hybrid parameters, and the [b] form of the ABCD-parameters is the matrix inverse of the [a] form. That is,

{\displaystyle {\begin{aligned}\left[\mathbf {y} \right]&=\left[\mathbf {z} \right]^{-1}\\\left[\mathbf {g} \right]&=\left[\mathbf {h} \right]^{-1}\\\left[\mathbf {b} \right]&=\left[\mathbf {a} \right]^{-1}\end{aligned}}}

Networks with more than two ports

While two port networks are very common (e.g., amplifiers and filters), other electrical networks such as directional couplers and circulators have more than 2 ports. The following representations are also applicable to networks with an arbitrary number of ports:

For example, three-port impedance parameters result in the following relationship:

${\displaystyle {\begin{bmatrix}V_{1}\\V_{2}\\V_{3}\end{bmatrix}}={\begin{bmatrix}Z_{11}&Z_{12}&Z_{13}\\Z_{21}&Z_{22}&Z_{23}\\Z_{31}&Z_{32}&Z_{33}\end{bmatrix}}{\begin{bmatrix}I_{1}\\I_{2}\\I_{3}\end{bmatrix}}}$

However the following representations are necessarily limited to two-port devices:

• Hybrid (h) parameters
• Inverse hybrid (g) parameters
• Transmission (ABCD) parameters
• Scattering transfer (T) parameters

Collapsing a two-port to a one port

A two-port network has four variables with two of them being independent. If one of the ports is terminated by a load with no independent sources, then the load enforces a relationship between the voltage and current of that port. A degree of freedom is lost. The circuit now has only one independent parameter. The two-port becomes a one-port impedance to the remaining independent variable.

For example, consider impedance parameters

${\displaystyle {\begin{bmatrix}V_{1}\\V_{2}\end{bmatrix}}={\begin{bmatrix}z_{11}&z_{12}\\z_{21}&z_{22}\end{bmatrix}}{\begin{bmatrix}I_{1}\\I_{2}\end{bmatrix}}}$

${\displaystyle V_{2}=-Z_{L}I_{2}\,}$

The negative sign is because the positive direction for I2 is directed into the two-port instead of into the load. The augmented equations become

{\displaystyle {\begin{aligned}V_{1}&=Z_{11}I_{1}+Z_{12}I_{2}\\-Z_{L}I_{2}&=Z_{21}I_{1}+Z_{22}I_{2}\end{aligned}}}

The second equation can be easily solved for I2 as a function of I1 and that expression can replace I2 in the first equation leaving V1 ( and V2 and I2 ) as functions of I1

{\displaystyle {\begin{aligned}I_{2}&=-{\frac {Z_{21}}{Z_{L}+Z_{22}}}I_{1}\\V_{1}&=Z_{11}I_{1}-{\frac {Z_{12}Z_{21}}{Z_{L}+Z_{22}}}I_{1}\\&=\left(Z_{11}-{\frac {Z_{12}Z_{21}}{Z_{L}+Z_{22}}}\right)I_{1}=Z_{\mathrm {in} }I_{1}\end{aligned}}}

So, in effect, I1 sees an input impedance ${\displaystyle Z_{\mathrm {in} }\,}$ and the two-port's effect on the input circuit has been effectively collapsed down to a one-port; i.e., a simple two terminal impedance.

Notes

1. The emitter-leg resistors counteract any current increase by decreasing the transistor VBE. That is, the resistors RE cause negative feedback that opposes change in current. In particular, any change in output voltage results in less change in current than without this feedback, which means the output resistance of the mirror has increased.
2. The double vertical bar denotes parallel connection of the resistors: ${\displaystyle R_{1}\|R_{2}=1/(1/R_{1}+1/R_{2})}$.

Related Research Articles

In physics, the Lorentz transformations are a one-parameter family of linear transformations from a coordinate frame in space time to another frame that moves at a constant velocity, the parameter, within the former. The transformations are named after the Dutch physicist Hendrik Lorentz. The respective inverse transformation is then parametrized by the negative of this velocity.

In probability theory and statistics, the multivariate normal distribution, multivariate Gaussian distribution, or joint normal distribution is a generalization of the one-dimensional (univariate) normal distribution to higher dimensions. One definition is that a random vector is said to be k-variate normally distributed if every linear combination of its k components has a univariate normal distribution. Its importance derives mainly from the multivariate central limit theorem. The multivariate normal distribution is often used to describe, at least approximately, any set of (possibly) correlated real-valued random variables each of which clusters around a mean value.

Kinematics is a branch of classical mechanics that describes the motion of points, bodies (objects), and systems of bodies without considering the forces that caused the motion. Kinematics, as a field of study, is often referred to as the "geometry of motion" and is occasionally seen as a branch of mathematics. A kinematics problem begins by describing the geometry of the system and declaring the initial conditions of any known values of position, velocity and/or acceleration of points within the system. Then, using arguments from geometry, the position, velocity and acceleration of any unknown parts of the system can be determined. The study of how forces act on bodies falls within kinetics, not kinematics. For further details, see analytical dynamics.

In mechanics and geometry, the 3D rotation group, often denoted SO(3), is the group of all rotations about the origin of three-dimensional Euclidean space R3 under the operation of composition. By definition, a rotation about the origin is a transformation that preserves the origin, Euclidean distance, and orientation. Every non-trivial rotation is determined by its axis of rotation and its angle of rotation. Composing two rotations results in another rotation; every rotation has a unique inverse rotation; and the identity map satisfies the definition of a rotation. Owing to the above properties, the set of all rotations is a group under composition. Rotations are not commutative, making it a nonabelian group. Moreover, the rotation group has a natural structure as a manifold for which the group operations are smoothly differentiable; so it is in fact a Lie group. It is compact and has dimension 3.

In mathematics, the Kronecker delta is a function of two variables, usually just non-negative integers. The function is 1 if the variables are equal, and 0 otherwise:

In the mathematical field of differential geometry, a metric tensor is a type of function which takes as input a pair of tangent vectors v and w at a point of a surface and produces a real number scalar g(v, w) in a way that generalizes many of the familiar properties of the dot product of vectors in Euclidean space. In the same way as a dot product, metric tensors are used to define the length of and angle between tangent vectors. Through integration, the metric tensor allows one to define and compute the length of curves on the manifold.

Acoustic impedance and specific acoustic impedance are measures of the opposition that a system presents to the acoustic flow resulting from an acoustic pressure applied to the system. The SI unit of acoustic impedance is the pascal second per cubic metre or the rayl per square metre, while that of specific acoustic impedance is the pascal second per metre or the rayl. In this article the symbol rayl denotes the MKS rayl. There is a close analogy with electrical impedance, which measures the opposition that a system presents to the electrical flow resulting from an electrical voltage applied to the system.

In control engineering, a state-space representation is a mathematical model of a physical system as a set of input, output and state variables related by first-order differential equations or difference equations. State variables are variables whose values evolve through time in a way that depends on the values they have at any given time and also depends on the externally imposed values of input variables. Output variables’ values depend on the values of the state variables.

A network, in the context of electronics, is a collection of interconnected components. Network analysis is the process of finding the voltages across, and the currents through, every component in the network. There are many different techniques for calculating these values. However, for the most part, the applied technique assumes that the components of the network are all linear. The methods described in this article are only applicable to linear network analysis, except where explicitly stated.

In linear algebra, a coordinate vector is a representation of a vector as an ordered list of numbers that describes the vector in terms of a particular ordered basis. Coordinates are always specified relative to an ordered basis. Bases and their associated coordinate representations let one realize vector spaces and linear transformations concretely as column vectors, row vectors, and matrices, hence are useful in calculations.

In applied statistics, total least squares is a type of errors-in-variables regression, a least squares data modeling technique in which observational errors on both dependent and independent variables are taken into account. It is a generalization of Deming regression and also of orthogonal regression, and can be applied to both linear and non-linear models.

In mathematics, the conjugate gradient method is an algorithm for the numerical solution of particular systems of linear equations, namely those whose matrix is symmetric and positive-definite. The conjugate gradient method is often implemented as an iterative algorithm, applicable to sparse systems that are too large to be handled by a direct implementation or other direct methods such as the Cholesky decomposition. Large sparse systems often arise when numerically solving partial differential equations or optimization problems.

Scattering parameters or S-parameters describe the electrical behavior of linear electrical networks when undergoing various steady state stimuli by electrical signals.

In physics, the gyration tensor is a tensor that describes the second moments of position of a collection of particles

In geometry, various formalisms exist to express a rotation in three dimensions as a mathematical transformation. In physics, this concept is applied to classical mechanics where rotational kinematics is the science of quantitative description of a purely rotational motion. The orientation of an object at a given instant is described with the same tools, as it is defined as an imaginary rotation from a reference placement in space, rather than an actually observed rotation from a previous placement in space.

In the field of mathematical modeling, a radial basis function network is an artificial neural network that uses radial basis functions as activation functions. The output of the network is a linear combination of radial basis functions of the inputs and neuron parameters. Radial basis function networks have many uses, including function approximation, time series prediction, classification, and system control. They were first formulated in a 1988 paper by Broomhead and Lowe, both researchers at the Royal Signals and Radar Establishment.

An equivalent impedance is an equivalent circuit of an electrical network of impedance elements which presents the same impedance between all pairs of terminals as did the given network. This article describes mathematical transformations between some passive, linear impedance networks commonly found in electronic circuits.

An antimetric electrical network is an electrical network that exhibits anti-symmetrical electrical properties. The term is often encountered in filter theory, but it applies to general electrical network analysis. Antimetric is the diametrical opposite of symmetric; it does not merely mean "asymmetric". It is possible for networks to be symmetric or antimetric in their electrical properties without being physically or topologically symmetric or antimetric.

In control system theory, and various branches of engineering, a transfer function matrix, or just transfer matrix is a generalisation of the transfer functions of single-input single-output (SISO) systems to multiple-input and multiple-output (MIMO) systems. The matrix relates the outputs of the system to its inputs. It is a particularly useful construction for linear time-invariant (LTI) systems because it can be expressed in terms of the s-plane.

Dynamic Substructuring (DS) is an engineering tool used to model and analyse the dynamics of mechanical systems by means of its components or substructures. Using the dynamic substructuring approach one is able to analyse the dynamic behaviour of substructures separately and to later on calculate the assembled dynamics using coupling procedures. Dynamic substructuring has several advantages over the analysis of the fully assembled system:

References

1. Gray, §3.2, p. 172
2. Jaeger, §10.5 §13.5 §13.8
3. Jasper J. Goedbloed. "Reciprocity and EMC measurements" (PDF). EMCS. Retrieved 28 April 2014.
4. Nahvi, p.311.
5. Matthaei et al, pp. 7072.
6. Matthaei et al, p.27.
7. Matthaei et al, p.29.
8. 56 IRE 28.S2, p. 1543
9. AIEE-IRE committee report, p. 725
10. IEEE Std 218-1956
11. Matthaei et al, p.26.
12. Ghosh, p.353.
13. Farago, p.102.
14. Clayton, p.271.
15. Vasileska & Goodnick, p.137
16. Egan, pp.11-12
17. Carlin, p.304
18. Matthaei et al, p.44.
19. Egan, pp.12-15
20. Egan, pp.13-14
21. Farago, pp.122-127.
22. Ghosh, p.371.
23. Farago, p.128.
24. Ghosh, p.372.
25. Ghosh, p.373.
26. Farago, pp.128-134.

Bibliography

• Carlin, HJ, Civalleri, PP, Wideband circuit design, CRC Press, 1998. ISBN   0-8493-7897-4.
• William F. Egan, Practical RF system design, Wiley-IEEE, 2003 ISBN   0-471-20023-9.
• Farago, PS, An Introduction to Linear Network Analysis, The English Universities Press Ltd, 1961.
• Gray, P.R.; Hurst, P.J.; Lewis, S.H.; Meyer, R.G. (2001). Analysis and Design of Analog Integrated Circuits (4th ed.). New York: Wiley. ISBN   0-471-32168-0.
• Ghosh, Smarajit, Network Theory: Analysis and Synthesis, Prentice Hall of India ISBN   81-203-2638-5.
• Jaeger, R.C.; Blalock, T.N. (2006). Microelectronic Circuit Design (3rd ed.). Boston: McGrawHill. ISBN   978-0-07-319163-8.
• Matthaei, Young, Jones, Microwave Filters, Impedance-Matching Networks, and Coupling Structures, McGraw-Hill, 1964.
• Mahmood Nahvi, Joseph Edminister, Schaum's outline of theory and problems of electric circuits, McGraw-Hill Professional, 2002 ISBN   0-07-139307-2.
• Dragica Vasileska, Stephen Marshall Goodnick, Computational electronics, Morgan & Claypool Publishers, 2006 ISBN   1-59829-056-8.
• Clayton R. Paul, Analysis of Multiconductor Transmission Lines, John Wiley & Sons, 2008 ISBN   0470131543, 9780470131541.