• Signal conversion in linear parametric circuits. Signal transformations in parametric circuits. Implementation of parametric resistive elements

    4.1. Classification and characteristics

    parametric circuits

    Literature: [L.1], pp. 307-308

    [L.2], pp. 368-371

    Radio engineering circuits whose conversion operator depends on time are called parametric. The law of signal conversion in a parametric circuit is written by the expression:

    A parametric resistor, the resistance of which changes over time according to a given law and at the same time does not depend on the magnitude of the input signal, can be implemented on the basis of an inertia-free nonlinear element with a current-voltage characteristic, the sum of the converted signal and the control voltage is supplied to the input (Fig. 4.1 ).

    The position of operating point A on the characteristic is determined by the constant bias voltage. Since the signal voltage is much less than the bias voltage, such a weak signal can be considered a small increment in relation to and the resistance of the nonlinear element in relation to the signal is estimated by the differential resistance

    . (4.2)

    The reciprocal of , as is known, is called differential slope

    . (4.3)

    If, for example, the current-voltage characteristic of a nonlinear element is approximated by a polynomial:

    then, in accordance with (4.3), we obtain

    or, given that

    Current caused by useful signal

    Thus, with respect to the signal, condition (4.1) is true and, with respect to the signal, the nonlinear element behaves as linear, but with variable slope.

    An essential feature of a parametric resistor is that its resistance or transconductance can be negative. This occurs when choosing an operating point on the decreasing section of the current-voltage characteristic (point B in Fig. 4.1).

    Variable controlled capacity in parametric circuits are implemented using special semiconductor diodes called varicaps. The operation of these diodes is based on the following effect: if a voltage of reverse polarity is applied to the diode junction, then the separated charge in the blocking layer is a nonlinear function of the applied voltage. Addiction is called coulomb-volt characteristic

    where is the capacitance value.

    Just like the resistance of a resistor, capacitance can be static or differential. Differential capacitance is determined as follows

    . (4.5)

    Here is the initial blocking voltage of the varicap.

    When the voltage applied to a varicap (capacitor) changes, a current arises:

    Obviously, the greater the blocking voltage, the greater the magnitude of the reverse transition, the smaller the value.

    Variable controlled inductance in parametric circuits can be implemented on the basis of an inductor with a ferromagnetic core, the magnetic permeability of which depends on the magnitude of the bias current. However, due to the high inertia of the processes of magnetization reversal of the core material, variable controlled inductances have not found application in parametric radio circuits.

    Methods for analyzing processes in linear circuits (systems)

    When analyzing processes, it is necessary to determine the response of the circuit to an input signal in the form of a signal of a given shape. From the basics of circuit theory it is known that to analyze the passage of harmonic signals through linear circuits, Kirchhoff's laws, methods of loop currents and nodal potentials, the equivalent generator method and other simple methods are used. These methods are also applicable for analysis under random influence. However, in communication theory they deal with pulsed signals, which are more diverse in shape and spectral composition and are described by a large number of parameters. These chains are also complex in structure. When analyzing the impact of signals on such circuits, spectral and operator methods and the superposition integral method are used.

    Spectral method. The properties of linear circuits (four-terminal networks) can be determined using this parameter, as frequency transfer coefficient. To do this, it is necessary to consider the response of a linear two-port network to the input influence and evaluate their connection with each other.

    Let us introduce the concepts of complex amplitudes of input and output harmonic voltages with angular (circular) frequency with:

    The ratio of the complex amplitudes of the output and input harmonic voltages of the same frequency determines frequency gain(usually just - transmission coefficient) linear circuit (linear quadrupole):

    Gain Module TO( co) = |K(co)| called amplitude-frequency response(frequency response), and the argument cp(co) - phase-frequency characteristic(PFC) of a linear quadrupole. As a rule, the frequency response has one maximum, and the phase response varies monotonically depending on the frequency (Fig. 4.2).

    In the region of a certain frequency band, the response of the circuit to the input influence begins to decrease. Therefore, they use the concept bandwidth (working strip) - frequency regions where the modulus of the transmission coefficient TO(с) not less than 1/V2 = 0.707 of its maximum value. The most convenient in practice is the normalized transmission coefficient modulus K/K shks, the maximum value of which is 1. The value of 1/V2, by which the bandwidth of a linear circuit is determined, was not introduced by chance. The thing is,

    Rice. 4.2.

    A - frequency response; b- The phase response is that at the boundaries of the passband the modulus of the power transmission coefficient, equal to the ratio of the output and input powers, is halved. In Fig. 4.2, the passband is contained in the region from the lower co n to the upper co in frequency, and therefore its width Dso 0 = co in - co,. In practice it is often used cyclical frequency /= /(2). Then the circuit bandwidth

    where / and - lower, and / in - upper boundary cyclic frequencies.

    The issue of frequency transfer coefficient can be approached from another point of view. If a harmonic signal of unit amplitude, having a complex analytical model of the form, is supplied to the linear price input uBX(t)= e J(0t , then the signal at its output will be written as uBbai(t)= TO( Substituting these expressions into formula (4.1), after simple transformations we write the frequency transmission coefficient in the form of a differential equation

    According to formula (4.3), the frequency transmission coefficient of a linear circuit, in which the connection between the input and output signals is described by a differential equation with constant coefficients, is a fractional-rational function of the variable y co. In this case, the coefficients of this function coincide with the coefficients of the differential equation.

    Using frequency gain TO( co) you can determine the signal at the output of a linear quadrupole. Let at the input of a linear four-port network with a frequency transfer coefficient TO( co) there is a continuous signal of arbitrary shape in the form of voltage m input (?). Applying the direct Fourier transform (2.29), we determine the spectral density of the input signal 5 in (co). Then the spectral density of the signal at the output of the linear circuit

    Having carried out the inverse Fourier transform (2.30) from the spectral density (4.4), we write the output signal as

    Operator method. Along with the spectral method, the operator method is used, which is based on the representation of input and output signals by Laplace transforms. The term “operator method” was introduced by O. Heaviside. He proposed a symbolic method for solving linear differential equations that describe transient processes in linear circuits. Heaviside's method is based on replacing the differentiation operator d/dt complex parameter r, which transfers signal analysis from the time domain to the domain of complex quantities. Consider a complex or real analog signal u(t), defined at t> 0 and equal to zero at time t = 0.

    Laplace transform this signal is a function of a complex variable r, expressed by the integral

    Analytical recording of the signal u(t) called original, and the function U(p) - his Laplace image(simpler - image). Integral

    • (4.6) superficially resembles the direct Fourier transform (2.29). However, there is a fundamental difference between them. The integral of the direct Fourier transform (2.29) includes the imaginary frequency acous, and the Laplace integral
    • (4.6) is a complex operator that can be considered as complex frequency p= a + uso (a is the real component), in this case only positive time values ​​are considered t. Due to the multiplier e~w under the integral in formula (4.6) for U(p) The Laplace transform is also possible for non-integrable functions u(t).

    The use of the concept of complex frequency in the integral transform makes it more efficient than the Fourier transform. For example, using formula (2.29) it is impossible to directly determine the spectrum of the inclusion function a(?) = 1(0- However, for the same signal directly using formula (4.6) it is easy to find its operator image:

    or, because e~ a ‘°° = 0, we get

    From the above example, it is obvious that the increase in the efficiency of transformation (4.6) is due to the presence of the multiplier e -a/, which ensures the convergence of this integral even for signals that do not satisfy the condition for the convergence of the integral . The presence of this multiplier allows us to interpret the Laplace transform (4.6) as a representation of the signal in the form of a “spectrum” of damped oscillations e w e,w = = e (a+уe j (in symbolic form).

    The Laplace transform (4.6) has linear properties similar to the linearity property of the Fourier transform:

    Among other properties, we note a simpler image transformation when differentiating and integrating a signal compared to similar Fourier transforms. Simplification is not only due to the complexity of the operator r, but also with the fact that the originals are analyzed on an infinite interval.

    By analogy with the inverse Fourier transform, we introduce inverse integral Laplace transform, which is carried out using deductions:

    where a, is a real variable reflected on the complex plane.

    Solving differential equations using the operator method. The Laplace transform allows you to solve linear differential equations with constant coefficients. Let it be necessary to find a solution to the differential equation (4.1). Let us establish a number of assumptions:

    • input signal u BX (t) = 0 at t
    • the input signal contains only those functions for which Laplace transforms exist;
    • the initial conditions are zero, i.e. g/out (0) = 0.

    Let us introduce correspondences between the originals of the input and output signals and their Laplace images:

    Carrying out the Laplace transform of both sides of formula (4.1), we obtain

    In the theory of automatic systems, the factor before U Bblx (p) in formula (4.8) are denoted by Q(p), calling own operator system, and the factor in front U nx (p) - through R(p) and call impact operator.

    The operator method is based on the most important characteristic, which is the ratio of the images of the output and input signals:

    and called transfer function (operator transfer coefficient) linear circuit.

    Using equation (4.8), we find

    Comparison of formulas (4.3) and (4.9) shows that the function K(r) reflects the result of the analytical transfer of the complex frequency transmission coefficient /((co) from the imaginary axis jeo over the entire range of complex frequencies p = a + jco.

    If the transfer function is known K(r), then the output response of the circuit to a given input influence u nx (t) can be determined according to the following scheme:

    • record the input signal image uBX(t) -? U BX(p)
    • find output image 0 uyh (p) = K(p)U ux (p)
    • calculate output signal u ttblx(t) - 5 ? 0 out(r).

    Roots of the denominator p v p 2 > ->P p in formula (4.9), i.e. roots of function

    called poles transfer function K(r).

    Accordingly, the roots of the numerator z v z 2, z m functions K(r), those. roots of function

    characterized as bullets transfer function.

    In real electrical circuits p>t.

    When dividing the numerator by the denominator in formula (4.9), a constant factor appears K 0, and this equation takes the so-called zero-pole transfer function representation

    Actual odds values a p And b t differential equation (4.16) determines the following property of the poles and zeros of the transfer function of a linear quadripole: either all these numbers are real or form complex conjugate pairs.

    Rice. 4.3.

    Very often, a visual technique is used to display the zeros and poles of the transfer function on the complex plane a, . In this case, poles are usually designated by crosses, and zeros by circles. For example, in Fig. 4.3 the circle at the origin of coordinates shows zero, and the crosses 1 And 2 - poles of the transfer function of some oscillatory value. Poles 1 And 2 are negative, real and determine the difference of two damping exponentials. Complex conjugate poles 3 And 4 determine the oscillatory nature of the transfer function K(r) with the greater attenuation, the more to the left they are located, and with the greater the frequency of damped oscillations, the further they move up and down from the real axis a. The location of the poles in the left half-plane corresponds to the damped nature of the transfer function. The zeros of the transfer function can be located in both the left and right half-plane.

    Dynamic representation of linear circuits. Superposition integral method. The properties of linear circuits are often easier to evaluate by the way they respond to the influence of elementary signals. Two types of dynamic representation of linear circuits have found application. According to the first of them, to analyze the response of the circuit, rectangular pulses of duration D are used as elementary signals, in the limit tending to the delta function. These pulses are directly adjacent to each other and form a sequence inscribed in or described around the curve. In the second method, the elementary signals are step functions that appear in the form of switching functions at equal time intervals A. The height of each step is equal to the signal increment over time interval D.

    One of the elementary electrical signals used in analyzing the passage of various oscillations through linear circuits (four-terminal networks) is the delta function 5(?). Another elementary electrical signal in communication technology is the switching function a(?).

    The delta function and the inclusion function are related analytically. The result of differentiating the inclusion function is the delta function

    Respectively

    Example 4.1

    Let us find the derivative of the product of the exponential momentum and the inclusion function u(t) = e~ at v(t).

    Solution

    For function e~w at a point in time t = 0 e~ a "° = 1. Derivative As a result of the calculations, we obtain the following expression:

    Pulse and transient characteristics of a linear circuit. Linearity and stationarity make it easy to find the reaction of a linear system theoretically to any input signal, knowing only one function - the system’s response to a delta function applied to the input 8 (t). This reaction is called impulse response or convolution kernel linear circuit (system) and denote h(t). Various types of real impulse responses of linear circuits h v h 2 , h 3 shown in Fig. 4.4, A.


    Rice. 4.4.

    A- various types of pulse; b - transitional

    The response of a linear circuit to a unit function is step response g(t)(Fig. 4.4, b). Let us assume that it is necessary to determine the output signal and output (?) of a linear circuit (linear two-port network), if its impulse response is known h(t) and input signal uBX(t). Let us approximately replace the input signal curve u nx (t) a stepped line in the form of a set of fairly short rectangular pulses having the same duration At (Fig. 4.5, A).

    Rice. 4.5.

    A- input signal; b - pulse responses and output signal

    The generation of the output signal can be explained as follows. A fairly small “piece” of the input signal with a duration of At is supplied to the input of the circuit being analyzed. If we choose the pulse duration At to be infinitesimal, then the response of a linear circuit to the first rectangular pulse will be approximately equal to the response of the same circuit to the delta function (and this will be the impulse response), multiplied by the area (and nx (0) At) of the first pulse , i.e. u nx (0)Axh(t)(Fig. 4.5, b). The response of a linear circuit to the second pulse with sufficient accuracy is the product r/in ( Ax)Axh(t - At), where and in (At) At is the area of ​​this pulse, and the magnitude h(t- At) - impulse response of a linear circuit corresponding to a moment in time t= At. Therefore, for some arbitrary moment of time t = groin (p - the number of conditionally formed pulses per time interval ) the response of a linear circuit will be approximately expressed by the sum (dashed line in Fig. 4.5, b)

    If the pulse duration At consistently approaches zero, then a small time increment At turns into dx, and the operation of summation is transformed into the operation of integration over the variable m = kAx:

    For real linear circuits always h(t) = 0 at t

    This fundamental relationship in linear circuit theory is imposition integral, or Duhamel integral Let us remind you that

    integral (4.13) is called convolution two functions (see Chapter 2). So, a linear system convolves the input signal with its impulse response, resulting in an output signal. Formula (4.13) has a clear physical meaning: a linear stationary circuit, processing the input signal, carries out a weighted summation of all its instantaneous values ​​that existed “in the past”.

    Convolution technique. To calculate the convolution using expression (4.13), the impulse response function is reversed along its coordinate, i.e. is built in reverse time mode, and moves relative to the input signal function towards increasing values L At each current moment in time, the values ​​of both functions are multiplied, and the product is integrated within the impulse response window. The result obtained refers to the coordinate point opposite which the value of the impulse response /?(()) is located. In the theory of electrical circuits, another, equivalent form of the Duhamel integral is used:

    So, the linear system transforms with respect to the variable t functions included in formula (4.14). In this case, the input signal is converted into an output signal mout (?)> and the delta function 8(t- t) - into impulse response h(t- T). The function min(t) does not depend on the variable t and therefore remains unchanged. The result is a formula showing that the output signal of a linear system is equal to the convolution of the input signal with its impulse response:

    Let us determine the relationship between the impulse response and the frequency transmission coefficient of a linear circuit. Let's use the complex form of a harmonic signal of unit amplitude and in(?) = exp(/co?). Substituting this expression into formula (4.14) and taking it out of the integral sign, we find the response of the circuit:

    The integral in parentheses is a complex function of frequency

    and represents the transmission coefficient (here a formal replacement of t is made with t).

    Expression (4.15) establishes an extremely important fact - the frequency transfer coefficient and the impulse response of a linear circuit are related by a direct Fourier transform. It is also obvious that there is an inverse Fourier transform for the transmission coefficient and impulse response

    with which you can easily determine the impulse response of a circuit from its frequency transfer coefficient.

    Since there is a simple connection between 6(7t) and a(t) according to formulas (4.10) and (4.11), all conclusions for a linear circuit made using the delta function are easily transferred to the inclusion function. Using similar reasoning and calculations, it can be shown that it is possible to simply represent input and output signals using the enable function a(t) and transient response of a linear circuit g(t). Having broken the input signal (Fig. 4.6) into elementary switching functions D mst (7) (here A And - amplitude of an elementary input voltage jump) and proceeding in the same way as when deriving relation (4.12), we obtain another form of the Duhamel integral, which allows us to determine the signal at the output of a linear circuit:

    Rice. 4.6.

    In the theory of linear circuits, a certain connection has been established between impulse and transient characteristics. Since the transition characteristic neiiHg(?) is a response to the unit function ст(/,), which, in turn, is an integral of the delta function 8(7) (see formula (4.11)), then between the functions h(t.) And g(t) there is an integral relation

    Experimentally, the impulse response of a linear circuit can be constructed by applying a short pulse of unit area to its input and reducing the pulse duration while maintaining the area until the output signal stops changing. This will be the impulse response of the circuit.

    • Jean-Marie Duhamel (J. Duhamel, 1797-1872) - French mathematician.

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    Signal conversion by linear circuits with constant parameters

    1. General information

    5.1 Integrating type circuits (low pass filters)

    5.2 Differentiation type circuits (high pass filters)

    5.3 Frequency selective circuits

    Literature

    1. General information

    An electronic circuit is a set of elements that ensure the passage and conversion of direct and alternating currents over a wide frequency range. It includes sources of electrical energy (power supplies), its consumers and storage devices, as well as connecting wires. Circuit elements can be divided into active and passive.

    In active elements it is possible to transform currents or voltages and simultaneously increase their power. These include, for example, transistors, operational amplifiers, etc.

    In passive elements, the transformation of currents or voltages is not accompanied by an increase in power, but, as a rule, its decrease is observed.

    Sources of electrical energy are characterized by the magnitude and direction of the electromotive force (emf) and the value of internal resistance. When analyzing electronic circuits, the concepts of ideal emf sources (generators) are used. E g (Fig. 1, a) and current I d (Fig. 1, b). They are divided into emf sources. (voltage sources) and current sources, called emf generators, respectively. (voltage generators) and current generators.

    Under the emf source understand such an idealized power source, the emf of which does not depend on the current flowing through it. Internal resistance R g of this idealized power supply is zero

    A current generator is an idealized power source that delivers current I g in the load, independent of the value of its resistance R n. In order for the current I g current source did not depend on load resistance R n, its internal resistance and its emf. theoretically should tend to infinity.

    Real voltage sources and current sources have internal resistance R g of finite value (Fig. 2).

    Passive elements of radio engineering circuits include electrical resistances (resistors), capacitors and inductors.

    The resistor is an energy consumer. The main parameter of a resistor is active resistance R. Resistance is expressed in ohms (Ohms), kiloohms (kOhms) and megohms (MOhms).

    Energy storage devices include a capacitor (electrical energy storage) and an inductor (magnetic energy storage).

    The main parameter of a capacitor is capacitance WITH. Capacitance is measured in farads (F), microfarads (µF), nanofarads (nF), picofarads (pF).

    The main parameter of an inductor is its inductance L. The inductance value is expressed in henry (H), millihenry (mH), microhenry (µH) or nanohenry (nH).

    When analyzing circuits, it is usually assumed that all these elements are ideal, for which the following relationships between the voltage drop are valid: u on the element and the current flowing through it i:

    If the element parameters R, L And WITH do not depend on external influences (voltage and current) and cannot increase the energy of the signal acting in the circuit, then they are called not only passive, but also linear elements. Circuits containing such elements are called passive linear circuits, linear circuits with constant parameters, or stationary circuits.

    A circuit in which active resistance, capacitance and inductance are assigned to certain sections of it is called a circuit with lumped parameters. If the parameters of a circuit are distributed along it, it is considered a distributed circuit.

    The parameters of circuit elements can change over time according to a certain law as a result of additional influences not related to voltages or currents in the circuit. Such elements (and the chains made up of them) are called parametric:

    Parametric elements include a thermistor, the resistance of which is a function of temperature, a powder carbon microphone with resistance controlled by air pressure, etc.

    Elements whose parameters depend on the magnitude of currents or voltages passing through them on the elements, and the relationships between currents and voltages are described by nonlinear equations, are called nonlinear, and circuits containing such elements are called nonlinear circuits.

    The processes occurring in circuits with lumped parameters are described by corresponding differential equations that connect the input and output signals through the circuit parameters.

    Linear differential equation with constant coefficients a 0 ,a 1 ,a 2 …a n,b 0 ,b 1 ,..,b m characterizes a linear circuit with constant parameters

    Linear differential equations with variable coefficients describe linear circuits with variable parameters.

    Finally, processes occurring in nonlinear circuits are described by nonlinear differential equations.

    In linear parametric systems, at least one of the parameters changes according to a given law. The result of signal conversion by such a system can be obtained by solving the corresponding differential equation with variable coefficients connecting the input and output signals.

    2. Properties of linear circuits with constant parameters

    As already indicated, processes occurring in linear circuits with constant lumped parameters are described by linear differential equations with constant coefficients. Let us consider the method of composing such equations using the example of a simple linear circuit consisting of series-connected elements R, L And C(Fig. 3). The circuit is excited by an ideal voltage source of arbitrary shape u(t). The task of the analysis is to determine the current flowing through the elements of the circuit.

    According to Kirchhoff's second law, voltage u(t) is equal to the sum of the voltage drops across the elements R, L And C

    Ri+L = u(t).

    Differentiating this equation, we get

    The solution of the resulting inhomogeneous linear differential equation allows us to determine the desired reaction of the circuit - i(t).

    The classical method of analyzing signal conversion by linear circuits is to find a general solution to such equations, equal to the sum of the particular solution of the original inhomogeneous equation and the general solution of the homogeneous equation.

    The general solution of a homogeneous differential equation does not depend on external influence (since the right side of the original equation, characterizing this influence, is taken equal to zero) and is entirely determined by the structure of the linear chain and the initial conditions. Therefore, the process described by this component of the general solution is called a free process, and the component itself is called a free component.

    A particular solution to an inhomogeneous differential equation is determined by the type of exciting function u(t). Therefore, it is called the forced (forced) component, which indicates its complete dependence on external excitation.

    Thus, the process occurring in the chain can be considered as consisting of two overlapping processes - a forced one, which seemed to occur immediately, and a free one, which takes place only during the transition regime. Thanks to the free components, a continuous approach to the forced (stationary) mode (state) of the linear circuit is achieved in the transient process. In a steady state, the law of changes in all currents and voltages in a linear circuit, up to constant values, coincides with the law of changes in the voltage of an external source.

    One of the most important properties of linear circuits, resulting from the linearity of the differential equation describing the behavior of the circuit, is the validity of the principle of independence or superposition. The essence of this principle can be formulated as follows: when several external forces act on a linear chain, the behavior of the chain can be determined by superimposing the solutions found for each of the forces separately. In other words, in a linear chain the sum of the reactions of this chain from various influences coincides with the reaction of the chain from the sum of the influences. It is assumed that the chain is free of initial energy reserves.

    Another fundamental property of linear circuits follows from the theory of integration of linear differential equations with constant coefficients. For any, no matter how complex, influence in a linear circuit with constant parameters, no new frequencies arise. This means that none of the signal transformations that involve the appearance of new frequencies (i.e., frequencies not present in the spectrum of the input signal) can, in principle, be carried out using a linear circuit with constant parameters.

    3. Analysis of signal conversion by linear circuits in the frequency domain

    The classical method of analyzing processes in linear circuits is often associated with the need to carry out cumbersome transformations.

    An alternative to the classical method is the operator (operational) method. Its essence consists in the transition through an integral transformation over the input signal from a differential equation to an auxiliary algebraic (operational) equation. Then a solution to this equation is found, from which, using an inverse transformation, a solution to the original differential equation is obtained.

    The Laplace transform is most often used as an integral transform, which for a function s(t) is given by the formula:

    Where p- complex variable: . Function s(t) is called the original, and the function S(p) - her image.

    The reverse transition from the image to the original is carried out using the inverse Laplace transform

    Having performed the Laplace transform of both sides of the equation (*), we obtain:

    The ratio of the Laplace images of the output and input signals is called the transfer characteristic (operator transfer coefficient) of a linear system:

    If the transfer characteristic of the system is known, then to find the output signal from a given input signal it is necessary:

    · - find the Laplace image of the input signal;

    · - find the Laplace image of the output signal using the formula

    · - according to the image S out ( p) find the original (circuit output signal).

    As an integral transformation for solving a differential equation, the Fourier transform can also be used, which is a special case of the Laplace transform when the variable p contains only the imaginary part. Note that in order for the Fourier transform to be applied to a function, it must be absolutely integrable. This limitation is removed in the case of the Laplace transform.

    As is known, the direct Fourier transform of the signal s(t), given in the time domain, is the spectral density of this signal:

    Having performed the Fourier transform of both sides of equation (*), we obtain:

    The ratio of the Fourier images of the output and input signals, i.e. the ratio of the spectral densities of the output and input signals is called the complex transmission coefficient of a linear circuit:

    If the linear system is known, then the output signal for a given input signal is found in the following sequence:

    · determine the spectral density of the input signal using the direct Fourier transform;

    · determine the spectral density of the output signal:

    Using the inverse Fourier transform, the output signal is found as a function of time

    If a Fourier transform exists for the input signal, then the complex transfer coefficient can be obtained from the transfer characteristic by replacing r on j.

    Analysis of signal conversion in linear circuits using complex gain is called the frequency domain analysis method (spectral method).

    In practice TO(j) are often found using circuit theory methods based on circuit diagrams, without resorting to drawing up a differential equation. These methods are based on the fact that, under harmonic influence, the complex transmission coefficient can be expressed as the ratio of the complex amplitudes of the output and input signals

    linear circuit signal integrating

    If the input and output signals are voltages, then K(j) is dimensionless, if current and voltage, respectively, then K(j) characterizes the frequency dependence of the resistance of a linear circuit, if voltage and current, then the frequency dependence of conductivity.

    Complex transmission coefficient K(j) linear circuit connects the spectra of the input and output signals. Like any complex function, it can be represented in three forms (algebraic, exponential and trigonometric):

    where is the dependence on the module frequency

    Dependence of phase on frequency.

    In the general case, the complex transmission coefficient can be depicted on the complex plane, plotting along the axis of real values, along the axis of imaginary values. The resulting curve is called the complex transmission coefficient hodograph.

    In practice, most dependencies TO() And k() are considered separately. In this case, the function TO() is called the amplitude-frequency response (AFC), and the function k() - phase-frequency response (PFC) of the linear system. We emphasize that the connection between the spectrum of the input and output signals exists only in the complex region.

    4. Analysis of signal conversion by linear circuits in the time domain

    The principle of superposition can be used to determine the response, deprived of the initial energy reserves of a linear circuit, to an arbitrary input stimulus. Calculations in this case turn out to be the simplest if we proceed from the representation of the exciting signal as a sum of standard components of the same type, having first studied the reaction of the circuit to the selected standard component. A unit function (unit step) 1( t - t 0) and delta pulse (unit pulse) ( t - t 0).

    The response of a linear circuit to a single step is called its transient response h(t).

    The response of a linear circuit to a delta pulse is called the impulse response g(t) of that circuit.

    Since a unit jump is an integral of the delta impulse, then the functions h(t) And g(t) are related to each other by the following relationships:

    Any input signal of a linear circuit can be represented as a collection of delta pulses multiplied by the value of the signal at times corresponding to the position of these pulses on the time axis. In this case, the relationship between the output and input signals of the linear circuit is given by the convolution integral (Duhamel integral):

    The input signal can also be represented as a set of unit jumps, taken with weights corresponding to the derivative of the signal at the point of origin of the unit jump. Then

    Analyzing signal conversion using impulse or step response is called by time domain analysis method (superposition integral method).

    The choice of a time or spectral method for analyzing signal conversion by linear systems is dictated mainly by the convenience of obtaining initial data about the system and the ease of calculations.

    The advantage of the spectral method is that it operates with the spectra of signals, as a result of which it is possible, at least qualitatively, to make a judgment about the change in the spectral density of the input signal about the change in its shape at the output of the system. When using the time domain analysis method, in general, it is extremely difficult to make such a qualitative assessment

    5. The simplest linear circuits and their characteristics

    Since the analysis of linear circuits can be carried out in the frequency or time domain, the result of signal conversion by such systems can be interpreted in two ways. Time domain analysis allows you to find out the change in the shape of the input signal. In the frequency domain, this result will look like a transformation over a function of frequency, leading to a change in the spectral composition of the input signal, which ultimately determines the shape of the output signal, in the time domain - as a corresponding transformation over a function of time.

    The characteristics of the simplest linear circuits are presented in Table 4.1.

    5.1 Integrating type circuits (low pass filters)

    Signal conversion according to the law

    Where m- proportionality coefficient, - value of the output signal at the moment t= 0 is called signal integration.

    The operation of integrating unipolar and bipolar rectangular pulses performed by an ideal integrator is illustrated in Fig. 4.

    The complex transmission coefficient of such a device amplitude-frequency response phase-frequency response transient response h(t) = t, for t 0.

    An ideal element for integrating input current i is an ideal capacitor (Fig. 5), for which

    Usually the task is to integrate the output voltage. To do this, it is enough to convert the input voltage source U input into the current generator i. A result close to this can be obtained if a resistor of sufficiently high resistance is connected in series with the capacitor (Fig. 6), at which the current i = (U in - U out)/ R almost independent of voltage U exit This will be true provided U out U input Then the expression for the output voltage (at zero initial conditions U out (0) = 0)

    can be replaced by the approximate expression

    where is the algebraic (i.e., taking into account the sign) area under the signal expressed by a certain integral on the interval (0, t), is the result of accurate signal integration.

    The degree of approximation of the real output signal to the function depends on the degree to which the inequality is satisfied U out U input or, which is almost the same thing, on the degree to which the inequality is satisfied U input . The value is inversely proportional to the value = R.C., which is called the time constant R.C.- chains. Therefore, to be able to use RC- as an integrating circuit, it is necessary that the time constant be sufficiently large.

    Complex transmission coefficient R.C.-integrating type circuits

    Comparing these expressions with the expressions for the ideal integrator, we find that for satisfactory integration it is necessary to satisfy condition "1.

    This inequality must be satisfied for all components of the input signal spectrum, including the smallest ones.

    Step response R.C.- integrating type circuits

    Thus, an integrating type RC circuit can perform signal conversion. However, very often there is a need to separate electrical oscillations of different frequencies. This problem is solved using electrical devices called filters. From the spectrum of electrical oscillations applied to the input of the filter, it selects (passes to the output) oscillations in a given frequency range (called the passband), and suppresses (weaken) all other components. According to the type of frequency response, filters are distinguished:

    - low frequencies, transmitting oscillations with frequencies no higher than a certain cutoff frequency 0 (passband? = 0 0);

    - treble, transmitting vibrations with frequencies above 0 (bandwidth? = 0);

    - strip, which transmit vibrations in a finite frequency range 1 2 (bandwidth? = 1 2);

    - rejector barriers, delaying oscillations in a given frequency band (stopband? = 1 2).

    Type of frequency response R.C.-integrating type circuits (Figure 4.6. b) shows that we are dealing with a circuit that effectively passes low frequencies. That's why R.C. This type of circuit can be classified as a low pass filter (LPF). With an appropriate choice of time constant, it is possible to significantly attenuate (filter) the high-frequency components of the input signal and practically isolate the constant component (if any). The cutoff frequency of such a filter is taken to be the frequency at which, i.e. the signal power transmission coefficient is reduced by 2 times. This frequency is often called cutoff frequency With (cutoff frequency 0 ). Cutoff frequency

    Additional phase shift introduced R.C.-integrating type circuit at frequency c, is - /4 .

    Integrating type circuits also include LR- circuit with resistance at the output (Fig. 6). Time constant of such a circuit = L/R.

    5.2 Differentiation type circuits (high pass filters)

    Differentiating is a circuit for which the output signal is proportional to the derivative of the input signal

    Where m- proportionality coefficient. Complex transmission coefficient of an ideal differentiating device amplitude-frequency response phase-frequency response transient response h(t) = (t).

    An ideal element for converting voltage applied to it into current I, varying proportionally to the derivative is an ideal capacitor (Fig. 4.7).

    To obtain a voltage proportional to the input voltage, it is enough to convert the current flowing in the circuit i into a voltage proportional to this current. To do this, just connect a resistor in series with the capacitor R(Fig. 8, b) so low resistance that the law of current change will hardly change ( i ? CdU input/ dt).

    However, in reality for R.C.- the circuit shown in Fig. 4.8, A, output signal

    and approximate equality U in ( t) ? RCdU input/ dt will be fair only if

    Taking into account the previous expression, we get:

    The fulfillment of this inequality will be facilitated by a decrease in the time constant = R.C., but at the same time the magnitude of the output signal will decrease U out, which is also proportional.

    More detailed analysis of the possibility of use R.C.-circuits as a differentiating circuit can be carried out in the frequency domain.

    Complex transmission coefficient for R.C.-chain of differentiating type is determined from the expression

    Frequency response and phase response (Fig. 4.8, V) are given accordingly by the expressions:

    Comparing the last expressions with the frequency response and phase response of an ideal differentiator, we can conclude that in order to differentiate the input signal, the inequality must be satisfied. It must be satisfied for all frequency components of the input signal spectrum.

    Step response R.C.- differentiating type chains

    The nature of the behavior of the frequency response R.C.-differentiation type circuit shows that such a circuit effectively passes high frequencies, so it can be classified as a high pass filter (HPF). The cutoff frequency of such a filter is taken to be the frequency at which. She is often called cutoff frequency With (cutoff frequency 0 ). Cutoff frequency

    At large time constants f R.C.- differentiating-type circuits, the voltage across the resistor repeats the alternating component of the input signal, and its constant component is completely suppressed. R.C.-the chain in this case is called a dividing chain.

    Has the same characteristics R.L.- circuit (Fig. 4.8, b), the time constant of which f =L/ R.

    5.3 Frequency selective circuits

    Frequency-selective circuits pass to the output only vibrations with frequencies lying in a relatively narrow band around the central frequency. Such circuits are often called linear bandpass filters. The simplest bandpass filters are oscillatory circuits formed by elements L, C And R, and in real circuits the resistance R(loss resistance) is usually the active resistance of reactive elements.

    Oscillatory circuits, depending on the connection of their constituent elements in relation to the output terminals, are divided into serial and parallel.

    The diagram of a series oscillatory circuit, when the output signal is the voltage removed from the capacitor, is shown in Fig. 9, A.

    The complex transmission coefficient of such a circuit

    If in a series oscillatory circuit the voltage is removed from the inductance (Fig. 4.9, b), That

    At a certain frequency of input oscillations in a series oscillatory circuit, voltage resonance occurs, which is expressed in the fact that the reactances of capacitance and inductance become equal in magnitude and opposite in sign. In this case, the total resistance of the circuit becomes purely active, and the current in the circuit has a maximum value. Frequency that satisfies the condition

    called resonant frequency 0:

    Size:

    represents the resistance module of any of the reactive elements of the oscillatory circuit at the resonant frequency and is called the characteristic (wave) impedance of the circuit.

    The ratio of active resistance to characteristic resistance is called circuit attenuation:

    The reciprocal d value is called the circuit quality factor:

    At resonant frequency

    This means that the voltage on each of the reactive elements of the circuit at resonance in Q times the voltage of the signal source.

    When finding the quality factor of a real (included in any circuit) series oscillatory circuit, it is necessary to take into account the internal (output) resistance R from the input signal source (this resistance will be connected in series with the active resistance of the circuit) and the active resistance R n load (which will be connected in parallel to the output reactive element). Taking this into account, the equivalent quality factor

    It follows that the resonant properties of a series oscillating circuit are best manifested with low-resistance signal sources and with high-resistance loads.

    The general diagram of a parallel oscillatory circuit is shown in Fig. 10. In the above diagram, R is the active resistance of the inductance, R1 is the active resistance of the capacitor.

    The input signal of such a circuit can only be a current signal, since in the case when the signal source is a voltage generator, the circuit will be shunted.

    The case of greatest interest is when the resistance R 1 capacitor WITH direct current is equal to infinity. A diagram of such a circuit is shown in Fig. 4.10, b. In this case, the complex transfer coefficient

    The complex transfer coefficient of a parallel oscillatory circuit (i.e., the total resistance of the circuit) is real at the resonant frequency p, satisfying the condition

    where is the resonant frequency of the series oscillatory circuit.

    At resonant frequency p

    Note that at this frequency the currents flowing through the capacitor WITH and inductor L, shifted in phase by, equal in magnitude and in Q times the current I input of the signal source.

    Due to the finiteness of internal resistance R from the signal source, the quality factor of the parallel circuit decreases:

    It follows that the resonant properties of a parallel oscillatory circuit are best manifested with signal sources with a high output resistance ( R s "), i.e. current generators.

    For parallel oscillatory circuits with high quality factor used in practice, the active loss resistance R significantly less inductive reactance L, therefore for the complex coefficient K(j ) we will have:

    As follows from these expressions, the resonant frequency of a high-quality parallel oscillatory circuit

    The impulse response of such a circuit

    its transient response

    For an ideal parallel oscillating circuit (lossless circuit, i.e. R = 0)

    The passband of the oscillatory circuits is entered similarly to the passband R.C.-chains, i.e. as the frequency range within which the modulus of the complex transmission coefficient exceeds the level of the maximum (at resonance) value. With high quality factors of the circuits and small deviations (misalignments) of frequencies relative to the resonant frequency, the frequency response of the series and parallel oscillatory circuits are almost identical. This makes it possible to obtain, although an approximate, but quite acceptable in practice, relationship between the bandwidth and circuit parameters

    Literature

    Zaichik M.Yu. and others. Collection of educational and control tasks on the theory of electrical circuits. - M.: Energoizdat, 1981.

    Borisov Yu.M. Electrical engineering: textbook. manual for universities / Yu.M. Borisov, D.N. Lipatov, Yu.N. Zorin. - 3rd edition, revised. and additional ; Grif MO. - Minsk: Higher. school A, 2007. - 543 s.

    Grigorash O.V. Electrical engineering and electronics: textbook. for universities / O.V. Grigorash, G.A. Sultanov, D.A. Norms. - Vulture UMO. - Rostov n/d: Phoenix, 2008. - 462 s.

    Lotoreychuk E.A. Theoretical foundations of electrical engineering: textbook. for students institutions prof. education / E.A. Lotoreychuk. - Grif MO. - M.: Forum: Infra-M, 2008. - 316 p.

    Fedorchenko A. A. Electrical engineering with fundamentals of electronics: textbook. for students prof. schools, lyceums and students. colleges / A. A. Fedorchenko, Yu. G. Sindeev. - 2nd ed. - M.: Dashkov and K°, 2010. - 415 p.

    Kataenko Yu. K. Electrical engineering: textbook. allowance / Yu. K. Kataenko. - M.: Dashkov and Co.; Rostov n/d: Akademtsentr, 2010. - 287 p.

    Moskalenko V.V. Electric drive: Textbook. allowance for the environment. prof. education / V.V. Moskalenko. - M.: Masterstvo, 2000. - 366 p.

    Savilov G.V. Electrical engineering and electronics: a course of lectures / G.V. Savilov. - M.: Dashkov and K°, 2009. - 322 p.

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    MOSCOW STATE TECHNICAL UNIVERSITY OF CIVIL AVIATION

    Department of Basics of Radio Engineering and Information Security

    COURSE WORK

    Analysis of Linear Circuit Characteristics

    And linear signal conversions

    Completed:

    Supervisor:

    Ilyukhin Alexander Alekseevich

    Moscow 2015

    1. Objectives of the course work.3

    2. Individual task.3

    3.Calculations 4

    4. Program for calculating and constructing amplitude-frequency, phase-frequency, transient and impulse characteristics of a circuit for given parameters10

    5. Program for calculating and constructing the reaction of a given circuit to a given signal11

    6. Charts 13

    1. Objectives of the course work.

    1. Study the nature of transient processes in linear circuits.

    2. To consolidate analytical methods for calculating the frequency and time characteristics of linear circuits.

    3. Master superposition signal analysis.

    4. Master the superposition method of calculating reactions of linear circuits.

    5. Understand the influence of circuit parameters on the type of its reaction.

    2. Individual task.

    Option 27 (circuit No. 7, signal No. 3).

    Fig. 1. Electric circuit

    Fig.2. Signal

    E =2 V

    t and =10 µs

    R =4 kOhm

    C =1000 pF

    Operator transfer characteristic of the circuit;

    Complex frequency response of the circuit;

    Amplitude-frequency response of the circuit;

    Phase-frequency characteristic of the circuit;

    Transient response of the circuit;

    Impulse response of the circuit.

    2. Perform superposition signal analysis.

    4. Create a program for calculating and constructing the amplitude-frequency, phase-frequency, transient and impulse characteristics of a circuit for its given parameters.

    5. Create a program for calculating and constructing the reaction of a given circuit to a given signal.

    6. Calculate the characteristics and reaction of the circuit indicated in paragraphs. 4 and 5, build their graphs.

    3.Calculations

    3.1. Calculation of circuit characteristics

    1. Operator transfer characteristic

    Fig.3. Generalized circuit diagram

    For a given scheme:

    According to the formula:

    For a given circuit shown in Fig. 1,

    Where θ=RC – time constant.

    2. Complex frequency response

    The complex frequency response is determined from the relationship:

    3. Amplitude-frequency response (AFC)

    4. Phase frequency response (PFC)

    For this chain:

    5. Step response

    For this chain:

    Because , where x 1 and x 2 – roots of the equation x 2 + bx + c = 0,

    Passage of signals through resistive parametric circuits. Frequency conversion

    12.1 (O). An ideal EMF source creates a voltage (V) And= 1.5 cos 2π · l0 7 t. A resistive element with time-varying conductivity (Cm) is connected to the source terminals G(t) = 10 -3 + 2 10 -4 sin 2π l0 6 t. Find the amplitude of the current IT, having a frequency of 9.9 MHz.

    12.2(O). The long-wave broadcast receiver is designed to receive signals in the frequency range from f c min = 150 kHz to f c max = 375 kHz. Receiver intermediate frequency f pr = 465 kHz. Determine within what limits the local oscillator frequency should be adjusted f g of this receiver.

    12.3(OS). In a superheterodyne receiver, the local oscillator creates harmonic oscillations with a frequency f r = 7.5 MHz. Receiver intermediate frequency f pr = 465 kHz; Of the two possible frequencies of the received signal, the main receiving channel corresponds to the larger one, and the mirror channel - the lower frequency. To suppress the mirror channel, a single oscillating circuit tuned to the frequency of the main channel is switched on at the input of the frequency converter. Find the value of the quality factor Q this circuit, at which the attenuation of the mirror channel will be - 25 dB relative to the main receiving channel.

    12.4(O). The differential slope of the resistive parametric element included in the frequency converter changes according to the law S diff ( t) =S 0 +S 1 cos ω G t, Where S 0 ,S 1 - constant numbers, ω r is the angular frequency of the local oscillator. Assuming that the intermediate frequency ω known, find the signal frequencies ω s, at which the effect occurs at the output of the converter.

    12.5(R). The flow characteristic of a field-effect transistor, i.e. drain current dependence i c (mA) from gate-source control voltage And zi (B) at And zi ≥ -2 V, approximated by a quadratic parabola: i c = 7.5( u zi + 2) 2 . Local oscillator voltage is applied to the transistor input And zi = Um g cos ω G t. Find the law of change in time of differential slope S diff ( t) characteristics i c = f(And zi).

    12.6(UO). In relation to the conditions of Problem 12.5, select the amplitude of the local oscillator voltage Um g in such a way as to ensure the slope of the transformation S pr = 6 mA/V.

    12.7(O). The frequency converter uses a semiconductor diode, the current-voltage characteristic of which is described by the dependence (mA)

    Local oscillator voltage (V) is applied to the diode u g = 1.2 cos ω G t. Calculate Transform Slope S pr of this device.

    12.8(UO). In a diode frequency converter, which is described in problem 12.7, a voltage (V) is applied to the diode u(t) =U 0 + 1.2cos ω G t. Determine

    at what bias voltage U 0 < 0 крутизна преобразования составит величину 1.5 мА/В.

    12.9(OS). The circuit of a frequency converter based on a field-effect transistor is shown in Fig. I.12.1. Oscillatory circuit tuned to intermediate frequency ω pr = | ω With - ω g |. Resonant circuit impedance R res = 18 kOhm. The sum of the useful signal voltage (µV) is applied to the converter input u With ( t) = 50 cos ω c t and local oscillator voltage (V) u G ( t) = 0.8cos ω G t. The characteristics of the transistor are described in the conditions of problem 12.5. Find the amplitude Um pr output signal at intermediate frequency.

    Passage of signals through parametric reactive circuits. Parametric amplifiers

    12.10(R). Differential capacitance of a parametric diode (varactor) in the vicinity of the operating point U 0 depends on applied voltage And as follows: WITH diff ( u) =b 0 +b 1 (u-U 0), where b 0 (pF) and b 1 (pF/V) - known numerical coefficients. A voltage is applied to the varactor u=U 0 +Um cos ω 0 t. Get the formula describing the current i(t) through a varactor.

    12.11 (UO). The differential capacitance of the varactor is described by the expression C diff ( u) =b 0 +b 1 (u-U 0) +b 2 (u-U 0) 2 . Voltage is applied to the varactor terminals u=U 0 +Um cos ω 0 t. Calculate amplitude I 3 third harmonics of the current through the varactor, if f 0 = 10 GHz, Um=1.5 V, b 2 = 0.16 pF/V 2.

    12.12(O). Varactor has the following parameters: b 0 = 4 pF, b 2 = 0.25 pF/V 2. A high-frequency voltage with an amplitude is applied to the varactor Um = 0.4 V. Determine how many times the amplitude of the first harmonic of the current will increase I 1 if value Um will become equal to 3 V.

    12.13(UO). The capacitance of a parametric capacitor changes over time according to the law WITH(t) =WITH 0 exp (- t/τ) σ ( t), Where WITH 0, τ are constant values. A source of linearly increasing voltage is connected to the capacitor u(t) =atσ( t). Calculate the law of change over time of current i(t) in the capacitor.

    12.14 (UO). In relation to the conditions of problem 12.13, find the moment of time t 1, at which the instantaneous power consumed by the capacitor from the signal source is maximum, as well as the moment of time t 2, in which the maximum power is given by the capacitor to the external circuits.

    12.15(R). A single-circuit parametric amplifier is connected from the input side to an EMF source (generator) with an internal

    resistance R g = 560 Ohm. The amplifier operates on a resistive load with resistance R n = 400 Ohm. Find the value of the introduced conductivity G Vn, which provides power gain TOR= 25 dB.

    12.16(O). For the parametric amplifier described in Problem 12.15, find the critical value of the introduced conductance G vn cr, at which the system is on the threshold of self-excitation.

    12.17 (UO). A signal voltage is applied to the terminals of the controlled parametric capacitor u(t) =Um cos( ω c t+π/3). The capacitance of a capacitor changes over time according to the law C(t) =C 0" where φ n is the initial phase angle of pump oscillation. Select the smallest absolute value φ n, which provides zero value of introduced conductivity.

    12.18(O). In relation to the conditions of problem 12.17 for the parameter values WITH 0 = 0.3 pF, β = 0.25 and ω c = 2π · 10 9 s -1 calculate the largest absolute value of negative conductivity G vn max, as well as the smallest absolute phase angle sra, providing such a regime.

    12.19(R). A two-circuit parametric amplifier is designed to operate at a frequency f c = 2 GHz. Amplifier idle frequency f cold = 0.5 GHz. The varactor used in the amplifier changes its capacitance (pF) with pump frequency ω n by law WITH(t) = 2(1 + 0.15 cos ω n t). The signal source and the load device have the same active conductances G g = G n = 2 10 -3 See. Calculate the value of the resonant resistance of the idle circuit R rez.col, at which self-excitation occurs in the amplifier.