Difference between revisions of "Linear and Time Invariant Systems/Inverse Laplace Transform"

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{{BlaueBox|TEXT=   
 
{{BlaueBox|TEXT=   
 
$\text{Task:}$  This chapter deals with the following problem:  
 
$\text{Task:}$  This chapter deals with the following problem:  
*The  $p$–spectral function  $Y_{\rm L}(p)$   is given in  "pole-zero"  notation.  
+
*The  $p$–spectral function  $Y_{\rm L}(p)$   is given in  »pole-zero notation«.  
*The  '''inverse Laplace transform''', i.e. the associated time function  $y(t)$  is searched-for,  where the following notation should hold:
+
*The  »'''inverse Laplace transform'''«, i.e. the associated time function  $y(t)$  is searched-for,  where the following notation should hold:
 
:$$y(t) = {\rm L}^{-1}\{Y_{\rm L}(p)\}\hspace{0.05cm} , \hspace{0.3cm}{\rm briefly}\hspace{0.3cm}
 
:$$y(t) = {\rm L}^{-1}\{Y_{\rm L}(p)\}\hspace{0.05cm} , \hspace{0.3cm}{\rm briefly}\hspace{0.3cm}
 
  y(t) \quad \circ\!\!-\!\!\!-^{\hspace{-0.25cm}\rm L}\!\!\!-\!\!\bullet\quad Y_{\rm L}(p)\hspace{0.05cm} .$$}}
 
  y(t) \quad \circ\!\!-\!\!\!-^{\hspace{-0.25cm}\rm L}\!\!\!-\!\!\bullet\quad Y_{\rm L}(p)\hspace{0.05cm} .$$}}
 +
 +
[[File:EN_LZI_T_3_3_S1.png |right|frame|Prerequisites for the chapter "Inverse Laplace Transform"]]
  
  
[[File:EN_LZI_T_3_3_S1.png |right|frame|Prerequisites for the chapter "Inverse Laplace Transform"]]
 
<br>
 
 
The graph summarizes the prerequisites for this task.
 
The graph summarizes the prerequisites for this task.
  
*$H_{\rm L}(p)$&nbsp; describes the transfer function of the causal system and &nbsp;$Y_{\rm L}(p)$&nbsp; specifies the Laplace transform of the output signal &nbsp;$y(t)$&nbsp; considering the input signal &nbsp;$x(t)$&nbsp;. &nbsp;$Y_{\rm L}(p)$&nbsp; is characterized by &nbsp;$N$&nbsp; poles,&nbsp; by &nbsp;$Z ≤ N$&nbsp; zeros and by the constant &nbsp;$K.$  
+
*$H_{\rm L}(p)$&nbsp; describes the transfer function of the causal system and &nbsp;$Y_{\rm L}(p)$&nbsp; specifies the Laplace transform of the output signal &nbsp;$y(t)$&nbsp; considering the input signal &nbsp;$x(t)$&nbsp;. &nbsp;$Y_{\rm L}(p)$&nbsp; is characterized by &nbsp;$N$&nbsp; poles,&nbsp; by &nbsp;$Z ≤ N$&nbsp; zeros and by the constant &nbsp;$K.$
*Poles and zeros exhibit the properties mentioned in the&nbsp; [[Linear_and_Time_Invariant_Systems/Laplace_Transform_and_p-Transfer_Function#Properties_of_poles_and_zeros|last chapter]]:&nbsp; Poles are only allowed in the left &nbsp;$p$–half plane or on the imaginary axis;&nbsp; zeros are also allowed in the right &nbsp;$p$–half plane.  
+
*All singularities – this is the generic term for poles and zeros – are either real or exist as pairs of conjugate-complex singularities.&nbsp; Multiple poles and zeros are also allowed.  
+
*Poles and zeros exhibit the properties mentioned in the&nbsp; [[Linear_and_Time_Invariant_Systems/Laplace_Transform_and_p-Transfer_Function#Properties_of_poles_and_zeros|&raquo;last chapter&laquo;]]:&nbsp; Poles are only allowed in the left &nbsp;$p$–half plane or on the imaginary axis;&nbsp; zeros are also allowed in the right &nbsp;$p$–half plane.
*With the input &nbsp;$x(t) = δ(t)$ &nbsp; &rArr; &nbsp;  $X_{\rm L}(p) = 1$  &nbsp; &rArr; &nbsp;  $Y_{\rm L}(p) = H_{\rm L}(p)$, the output signal &nbsp;$y(t)$&nbsp; then describes the [[Linear_and_Time_Invariant_Systems/System_Description_in_Time_Domain#Impulse_response|impulse response]]  &nbsp;$h(t)$&nbsp; of the transmission system.&nbsp; For this purpose, only the singularities drawn in green in the graph may be used for computation.  
+
*A step function &nbsp;$x(t) = γ(t)$ &nbsp; &rArr; &nbsp;  $ X_{\rm L} = 1/p$&nbsp; at the input causes the output signal &nbsp;$y(t)$&nbsp; to be equal to the &nbsp;[[Linear_and_Time_Invariant_Systems/System_Description_in_Time_Domain#Step_response|step response]] &nbsp; $σ(t)$ of $H_{\rm L}(p)$&nbsp;.&nbsp; In addition to the singularities of &nbsp;$H_{\rm L}(p)$,&nbsp; the pole (shown in red in the graph) at &nbsp;$p = 0$&nbsp; must now also be taken into account for computation.  
+
*All&nbsp; &raquo;singularities&laquo;&nbsp; – this is the generic term for poles and zeros – are either real or exist as pairs of conjugate-complex singularities.&nbsp; Multiple poles and zeros are also allowed.
*Only signals for which &nbsp;$X_{ \rm L}(p)$&nbsp; can be expressed in pole-zero notation are possible as input &nbsp;$x(t)$&nbsp; (see the &nbsp;[[Linear_and_Time_Invariant_Systems/Laplace_Transform_and_p-Transfer_Function#Some_important_Laplace_correspondences|table]]&nbsp; in the chapter "Laplace Transform and $p$–Transfer Function"), for example a cosine or sine signal switched on at time &nbsp;$t = 0$&nbsp;.  
+
*So, a rectangle as input signal &nbsp;$x(t)\ \  ⇒ \ \ X_{\rm L}(p) = (1 - {\rm e}^{\hspace{0.05cm}p\hspace{0.05cm}\cdot \hspace{0.05cm} T})/p$&nbsp; is not possible in the approach described here.&nbsp; However, the rectangular response &nbsp;$y(t)$&nbsp; can be computed indirectly as the difference of two step responses.
+
*With the input &nbsp;$x(t) = δ(t)$ &nbsp; &rArr; &nbsp;  $X_{\rm L}(p) = 1$  &nbsp; &rArr; &nbsp;  $Y_{\rm L}(p) = H_{\rm L}(p)$, the output signal &nbsp;$y(t)$&nbsp; then describes the [[Linear_and_Time_Invariant_Systems/System_Description_in_Time_Domain#Impulse_response|&raquo;impulse response&laquo;]]  &nbsp;$h(t)$&nbsp; of the transmission system.&nbsp; For this purpose,&nbsp; only the singularities drawn in green in the graph may be used for computation.  
 +
 
 +
*A unit jump  function &nbsp;$x(t) = γ(t)$ &nbsp; &rArr; &nbsp;  $ X_{\rm L} = 1/p$&nbsp; at the input causes the output signal &nbsp;$y(t)$&nbsp; to be equal to the &nbsp;[[Linear_and_Time_Invariant_Systems/System_Description_in_Time_Domain#Step_response|&raquo;step response&laquo;]] &nbsp; $σ(t)$ of $H_{\rm L}(p)$&nbsp;.&nbsp; In addition to the singularities of &nbsp;$H_{\rm L}(p)$,&nbsp; the pole&nbsp; $($shown in red in the graph$)$&nbsp; at &nbsp;$p = 0$&nbsp; must now also be taken into account for computation.
 +
 +
*Possible as input &nbsp;$x(t)$&nbsp; are only signals for which &nbsp;$X_{ \rm L}(p)$&nbsp; can be expressed in pole-zero notation&nbsp; (see the &nbsp;[[Linear_and_Time_Invariant_Systems/Laplace_Transform_and_p-Transfer_Function#Some_important_Laplace_correspondences|$\text{table}$]]&nbsp; in the chapter &raquo;Laplace Transform and $p$–Transfer Function&raquo;$)$,&nbsp; for example a cosine or sine signal switched on at time &nbsp;$t = 0$&nbsp;.
 +
 +
*So,&nbsp; a rectangular signal &nbsp;$x(t)\ \  ⇒ \ \ X_{\rm L}(p) = (1 - {\rm e}^{\hspace{0.05cm}p\hspace{0.05cm}\cdot \hspace{0.05cm} T})/p$&nbsp; is not possible in the approach described here.&nbsp; However, the rectangular response &nbsp;$y(t)$&nbsp; can be computed indirectly as the difference of two step responses.
  
==Some results of the theory of functions==
+
==Some results of function theory==
 
<br>
 
<br>
In contrast to the&nbsp; [[Signal_Representation/Fourier_Transform_and_Its_Inverse#The_first_Fourier_integral|Fourier integrals]],&nbsp; which differ only slightly in the two directions of transformation,&nbsp; for&nbsp; "Laplace"&nbsp; the computation of &nbsp;$y(t)$&nbsp; from &nbsp;$Y_{\rm L}(p)$ – that is the inverse transformation – is
+
In contrast to the&nbsp; [[Signal_Representation/Fourier_Transform_and_Its_Inverse#The_first_Fourier_integral|&raquo;Fourier integrals&laquo;]],&nbsp; which differ only slightly in the two directions of transformation,&nbsp; for&nbsp; &raquo;Laplace&laquo;&nbsp; the computation of &nbsp;$y(t)$&nbsp; from &nbsp;$Y_{\rm L}(p)$ – that is the inverse transformation – is
*much more difficult than computing &nbsp;$Y_{\rm L}(p)$&nbsp; from &nbsp;$y(t)$,  
+
*much more difficult than computing &nbsp;$Y_{\rm L}(p)$&nbsp; from &nbsp;$y(t)$,
 +
 
*unresolvable or solvable only very laboriously by elementary means.
 
*unresolvable or solvable only very laboriously by elementary means.
  
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{{BlaueBox|TEXT=   
 
{{BlaueBox|TEXT=   
 
$\text{Definition:}$&nbsp;  
 
$\text{Definition:}$&nbsp;  
In general, the following holds for the&nbsp; '''inverse Laplace trans''':
+
In general, the following holds for the&nbsp; &raquo;'''inverse Laplace transform'''&laquo;:
 
:$$y(t) = {\rm L}^{-1}\{Y_{\rm L}(p)\}= \lim_{\beta \hspace{0.05cm}\rightarrow \hspace{0.05cm}\infty}  \hspace{0.15cm} \frac{1}{ {\rm j} \cdot 2 \pi}\cdot    \int_{ \alpha - {\rm j} \hspace{0.05cm}\cdot \hspace{0.05cm}2 \pi \beta } ^{\alpha+{\rm j}  \hspace{0.05cm}\cdot \hspace{0.05cm}2 \pi \beta}  Y_{\rm L}(p) \hspace{0.05cm}\cdot \hspace{0.05cm} {\rm e}^{\hspace{0.05cm}p \hspace{0.05cm}\cdot \hspace{0.05cm} t}\hspace{0.1cm}{\rm
 
:$$y(t) = {\rm L}^{-1}\{Y_{\rm L}(p)\}= \lim_{\beta \hspace{0.05cm}\rightarrow \hspace{0.05cm}\infty}  \hspace{0.15cm} \frac{1}{ {\rm j} \cdot 2 \pi}\cdot    \int_{ \alpha - {\rm j} \hspace{0.05cm}\cdot \hspace{0.05cm}2 \pi \beta } ^{\alpha+{\rm j}  \hspace{0.05cm}\cdot \hspace{0.05cm}2 \pi \beta}  Y_{\rm L}(p) \hspace{0.05cm}\cdot \hspace{0.05cm} {\rm e}^{\hspace{0.05cm}p \hspace{0.05cm}\cdot \hspace{0.05cm} t}\hspace{0.1cm}{\rm
 
  d}p \hspace{0.05cm} .$$
 
  d}p \hspace{0.05cm} .$$
*The integration is parallel to the imaginary axis.  
+
#The integration is parallel to the imaginary axis.  
*The real part &nbsp;$α$&nbsp; is to be chosen such that all poles are located to the left of the integration path.}}
+
#The real part &nbsp;$α$&nbsp; is to be chosen such that all poles are located to the left of the integration path.}}
  
  
 +
The left graph illustrates this line integral along the red dotted vertical &nbsp;${\rm Re}\{p\}= α$.&nbsp; This integral is solvable using &nbsp;[https://en.wikipedia.org/wiki/Jordan%27s_lemma &raquo;Jordan's lemma of complex analysis&laquo;].&nbsp; In this tutorial only a very short and simple summary of the approach is depicted:
 
[[File:EN_LZI_T_3_3_S2.png |right|frame|Line integral together with left and right circular integral]]
 
[[File:EN_LZI_T_3_3_S2.png |right|frame|Line integral together with left and right circular integral]]
 
+
The left graph illustrates this line integral along the red dotted vertical &nbsp;${\rm Re}\{p\}= α$.&nbsp; This integral is solvable using &nbsp;[https://en.wikipedia.org/wiki/Jordan%27s_lemma Jordan's lemma of complex analysis].&nbsp; In this tutorial only a very short and simple summary of the approach is depicted:
+
#The line integral can be divided into two circular integrals so that all poles are located in the left circular integral while the right circular integral may only contain zeros.  
*The line integral can be divided into two circular integrals so that all poles are located in the left circular integral while the right circular integral may only contain zeros.  
+
#According to the theory of functions, the right circular integral yields the time function &nbsp;$y(t)$&nbsp; for negative times.&nbsp;  
*According to the theory of functions, the right circular integral yields the time function &nbsp;$y(t)$&nbsp; for negative times.&nbsp; Due to causality, &nbsp;$y(t < 0)$&nbsp; must be identical to zero,&nbsp; but according to the fundamental theorem of the theory of functions this is only true if there are no poles in the right &nbsp;$p$–half-plane.  
+
#Due to causality, &nbsp;$y(t < 0)$&nbsp; must be identical to zero,&nbsp; but according to the fundamentals of function theorem this is only true if there are no poles in the right &nbsp;$p$–half-plane.  
*In contrast,&nbsp; the integral over the left semicircle yields the time function for &nbsp;$t ≥ 0$.&nbsp; This encloses all poles and can be computed using the&nbsp; "residue theorem"&nbsp; in a (relatively) simple way,&nbsp; as it will be shown in the next sections.  
+
#In contrast,&nbsp; the integral over the left semicircle yields the time function for &nbsp;$t ≥ 0$.&nbsp;  
 
+
#This encloses all poles and can be computed using the&nbsp; &raquo;'''residue theorem'''&laquo;&nbsp; in a&nbsp; $($relatively$)$&nbsp; simple way,&nbsp; as it will be shown in the next sections.  
 +
<br clear=all>
 
==Formulation of the residue theorem==
 
==Formulation of the residue theorem==
 
<br>
 
<br>
 
It is further assumed that the transfer function &nbsp;$Y_{\rm L}(p)$&nbsp; can be expressed in pole-zero notation  by  
 
It is further assumed that the transfer function &nbsp;$Y_{\rm L}(p)$&nbsp; can be expressed in pole-zero notation  by  
 
*the constant factor&nbsp; $K$,  
 
*the constant factor&nbsp; $K$,  
*the &nbsp;$Z$&nbsp; "zeros" &nbsp;$p_{{\rm o}i}$&nbsp; $(i = 1$, ... , $Z)$&nbsp; and  
+
*the &nbsp;$Z$&nbsp; &raquo;zeros&laquo; &nbsp;$p_{{\rm o}i}$&nbsp; $(i = 1$, ... , $Z)$&nbsp; and  
*the &nbsp;$N$&nbsp; "poles" &nbsp;$p_{{\rm x}i}$&nbsp; $(i = 1$, ... , $N$).  
+
*the &nbsp;$N$&nbsp; &raquo;poles&laquo; &nbsp;$p_{{\rm x}i}$&nbsp; $(i = 1$, ... , $N$).  
 
 
  
We also assume &nbsp;$Z < N$.
 
  
The number of distinguishable poles is denoted by &nbsp;$I$.&nbsp; Multiple poles are counted only once to determine &nbsp;$I$.&nbsp; Thus, the following holds for the&nbsp; [[Linear_and_Time_Invariant_Systems/Inverse_Laplace_Transform#Some_results_of_the_theory_of_functions|sketch]]&nbsp; in the last section considering the  double pole: &nbsp;  $N = 5$&nbsp; and &nbsp;$I = 4$.
+
We also assume &nbsp;$Z < N$.&nbsp; The number of&nbsp; &raquo;distinguishable poles&laquo;&nbsp; is denoted by &nbsp;$I$.&nbsp; Multiple poles are counted only once to determine &nbsp;$I$.&nbsp; Thus,&nbsp; the following holds for the&nbsp; [[Linear_and_Time_Invariant_Systems/Inverse_Laplace_Transform#Some_results_of_function_theory|$\text{sketch}$]]&nbsp; in the last section considering the  double pole: &nbsp;   
 +
:$$N = 5,\hspace{0.3cm} I = 4.$$
  
 
{{BlaueBox|TEXT=   
 
{{BlaueBox|TEXT=   
 
$\text{Residue Theorem:}$&nbsp;  
 
$\text{Residue Theorem:}$&nbsp;  
Considering the above conditions, the&nbsp; '''inverse Laplace transform'''&nbsp; of &nbsp;$Y_{\rm L}(p)$&nbsp; for times&nbsp; $t ≥ 0$&nbsp; is obtained as the sum of&nbsp; $I$&nbsp; natural oscillations of the poles,&nbsp; which are called the&nbsp; "residuals"&nbsp; – abbreviated as "Res":
+
Considering the above conditions,&nbsp; the&nbsp; &raquo;'''inverse Laplace transform'''&laquo;&nbsp; of &nbsp;$Y_{\rm L}(p)$&nbsp; for times&nbsp; $t ≥ 0$&nbsp; is obtained as the sum of&nbsp; $I$&nbsp; natural oscillations of the poles,&nbsp; which are called the&nbsp; &raquo;residuals&laquo;&nbsp; – abbreviated as&nbsp; $\rm Res$:
 
:$$y(t) = \sum_{i=1}^{I}{\rm Res} \bigg \vert _{p \hspace{0.05cm}= \hspace{0.05cm}p_{{\rm x}_i}} \hspace{-0.7cm}\{Y_{\rm L}(p)\cdot  {\rm e}^{p \hspace{0.05cm}t}\} \hspace{0.05cm} .$$
 
:$$y(t) = \sum_{i=1}^{I}{\rm Res} \bigg \vert _{p \hspace{0.05cm}= \hspace{0.05cm}p_{{\rm x}_i}} \hspace{-0.7cm}\{Y_{\rm L}(p)\cdot  {\rm e}^{p \hspace{0.05cm}t}\} \hspace{0.05cm} .$$
  
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In the next sections,&nbsp; the&nbsp; "residue theorem"&nbsp; is illustrated by three detailed examples corresponding to the three constellations in&nbsp; [[Linear_and_Time_Invariant_Systems/Laplace_Transform_and_p-Transfer_Function#Properties_of_poles_and_zeros| $\text{Example 3}$]]&nbsp; in the chapter&nbsp; "Laplace Transform and p-Transfer Function":  
+
In the next sections,&nbsp; the&nbsp; &raquo;residue theorem&laquo;&nbsp; is illustrated by three detailed examples corresponding to the three constellations in&nbsp; [[Linear_and_Time_Invariant_Systems/Laplace_Transform_and_p-Transfer_Function#Properties_of_poles_and_zeros|$\text{Example 3}$]]&nbsp; of chapter&nbsp; &raquo;Laplace transform and p-transfer function&laquo;:  
*So, we consider again the two-port network with an inductance &nbsp;$L = 25 \ \rm &micro;H$&nbsp; in the longitudinal branch as well as the the series connection of an ohmic resistance&nbsp; $R = 50 \ \rm Ω$&nbsp; and a capacitance&nbsp; $C$&nbsp; in the transverse branch.  
+
*So,&nbsp; we consider again the two-port network with an inductance &nbsp;$L = 25 \ \rm &micro;H$&nbsp; in the longitudinal branch as well as the the series connection of an ohmic resistance&nbsp; $R = 50 \ \rm Ω$&nbsp; and a capacitance&nbsp; $C$&nbsp; in the transverse branch.  
*For the latter,&nbsp; we again consider three different values,&nbsp; namely &nbsp;$C = 62.5 \ \rm nF$, &nbsp;$C = 8 \ \rm nF$&nbsp; and &nbsp;$C = 40 \ \rm nF$.  
+
 
 +
*For the latter,&nbsp; we consider three different values,&nbsp; namely &nbsp;$C = 62.5 \ \rm nF$, &nbsp;$C = 8 \ \rm nF$&nbsp; and &nbsp;$C = 40 \ \rm nF$.  
 +
 
 
*The following is always assumed: &nbsp;$x(t) = δ(t) \; ⇒  \; X_{\rm L}(p) = 1$ &nbsp; &rArr; &nbsp; $Y_{\rm L}(p) = H_{\rm L}(p)$  &nbsp; &rArr; &nbsp; the output signal&nbsp; $y(t)$&nbsp; is equal to the impulse response &nbsp;$h(t)$.
 
*The following is always assumed: &nbsp;$x(t) = δ(t) \; ⇒  \; X_{\rm L}(p) = 1$ &nbsp; &rArr; &nbsp; $Y_{\rm L}(p) = H_{\rm L}(p)$  &nbsp; &rArr; &nbsp; the output signal&nbsp; $y(t)$&nbsp; is equal to the impulse response &nbsp;$h(t)$.
  
 
==Aperiodically decaying impulse response==
 
==Aperiodically decaying impulse response==
 
<br>
 
<br>
The following is obtained for the&nbsp; $p$&ndash;transfer function computed in the section &nbsp;[[Linear_and_Time_Invariant_Systems/Laplace_Transform_and_p-Transfer_Function#Pole-zero_representation_of_circuits|pole-zero representation of circuits]]&nbsp; with the capacitance &nbsp;$C = 62.5 \ \rm nF$&nbsp; and the other numerical values given in the graph below:
+
The following is obtained for the&nbsp; $p$&ndash;transfer function computed in the section &nbsp;[[Linear_and_Time_Invariant_Systems/Laplace_Transform_and_p-Transfer_Function#Pole-zero_representation_of_circuits|&raquo;pole-zero representation of circuits&laquo;]]&nbsp; with the capacitance &nbsp;$C = 62.5 \ \rm nF$.&nbsp; The other numerical values are given in the graph below:
 
[[File: EN_LZI_T_3_3_S3a.png|right|frame|Aperiodically decaying impulse response]]
 
[[File: EN_LZI_T_3_3_S3a.png|right|frame|Aperiodically decaying impulse response]]
  
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Note the normalization of &nbsp;$p$, &nbsp;$K$ and also of all poles and zeros by the factor &nbsp;${\rm 10^6} · 1/\rm s$.
 
Note the normalization of &nbsp;$p$, &nbsp;$K$ and also of all poles and zeros by the factor &nbsp;${\rm 10^6} · 1/\rm s$.
  
The impulse response is composed of &nbsp;$I = N = 2$&nbsp; natural oscillations. For $t < 0$,&nbsp; these are equal to zero.
+
&rArr; &nbsp; The impulse response is composed of &nbsp;$I = N = 2$&nbsp; natural oscillations. For $t < 0$,&nbsp; these are equal to zero.
 
*The residual of the pole at &nbsp;$p_{{\rm x}1} =\  –0.4$&nbsp; yields the following time function:
 
*The residual of the pole at &nbsp;$p_{{\rm x}1} =\  –0.4$&nbsp; yields the following time function:
 
:$$h_1(t)  =  {\rm Res} \bigg |_{p \hspace{0.05cm}= \hspace{0.05cm}p_{{\rm x}1}} \hspace{-0.7cm}\{H_{\rm L}(p)\cdot {\rm e}^{p t}\}= H_{\rm L}(p)\cdot (p - p_{{\rm x}1})\cdot {\rm e}^{p \hspace{0.05cm}t} \bigg |_{p \hspace{0.05cm}= \hspace{0.05cm}p_{{\rm x}1}}$$
 
:$$h_1(t)  =  {\rm Res} \bigg |_{p \hspace{0.05cm}= \hspace{0.05cm}p_{{\rm x}1}} \hspace{-0.7cm}\{H_{\rm L}(p)\cdot {\rm e}^{p t}\}= H_{\rm L}(p)\cdot (p - p_{{\rm x}1})\cdot {\rm e}^{p \hspace{0.05cm}t} \bigg |_{p \hspace{0.05cm}= \hspace{0.05cm}p_{{\rm x}1}}$$
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The graph shows &nbsp;$h_1(t)$&nbsp; and &nbsp;$h_2(t)$&nbsp; as well as the sum signal &nbsp;$h(t)$.  
 
The graph shows &nbsp;$h_1(t)$&nbsp; and &nbsp;$h_2(t)$&nbsp; as well as the sum signal &nbsp;$h(t)$.  
*The normalization factor &nbsp;$1/T = 10^6 · \rm 1/s$ is taken into account here so that the time is normalized to &nbsp;$T = 1 \ \rm &micro; s$&nbsp;.  
+
#The normalization factor &nbsp;$1/T = 10^6 · \rm 1/s$&nbsp; is taken into account here so that the time is normalized to &nbsp;$T = 1 \ \rm &micro; s$&nbsp;.  
*For &nbsp;$t =0$,&nbsp; $T \cdot h(t=0) =  {32 }/ {15} -{2 }/ {15}= 2 \hspace{0.05cm}$&nbsp; is obtained as a result.  
+
#For &nbsp;$t =0$,&nbsp; $T \cdot h(t=0) =  {32 }/ {15} -{2 }/ {15}= 2 \hspace{0.05cm}$&nbsp; is obtained as a result.  
*For times &nbsp;$t > 2 \ \rm &micro; s$,&nbsp; the impulse response is negative&nbsp; (although only slightly and difficult to see in the graph).
+
#For times &nbsp;$t > 2 \ \rm &micro; s$,&nbsp; the impulse response is negative&nbsp; $($although only slightly and difficult to see in the graph$)$.
  
  
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[[File:EN_LZI_T_3_3_S3b.png|right|frame| Attenuated-oscillatory impulse response]]
 
[[File:EN_LZI_T_3_3_S3b.png|right|frame| Attenuated-oscillatory impulse response]]
 
   
 
   
*The zero is located at &nbsp;$p_{\rm o} = \ –2.5$.  
+
*The zero is located at &nbsp;$p_{\rm o} = \ –2.5$.
*$K = 2$&nbsp; holds and all numerical values are to be multiplied again by the factor &nbsp;$1/T$&nbsp; $(T = 1\ \rm &micro; s$).
+
 +
*$K = 2$&nbsp; holds  
 +
 
 +
*All numerical values are to be multiplied by factor &nbsp;$1/T$&nbsp; $(T = 1\ \rm &micro; s$).
  
  
When applying the residue theorem to this configuration the following is obtained:
+
Applying the residue theorem to this configuration then it is obtained:
 +
 
 
:$$h_1(t) =  K \cdot \frac {p_{\rm x 1} - p_{\rm o }} {p_{\rm x 1} - p_{\rm x 2}} \cdot  {\rm e}^{\hspace{0.05cm}p_{\rm x 1} \cdot \hspace{0.05cm}t} $$
 
:$$h_1(t) =  K \cdot \frac {p_{\rm x 1} - p_{\rm o }} {p_{\rm x 1} - p_{\rm x 2}} \cdot  {\rm e}^{\hspace{0.05cm}p_{\rm x 1} \cdot \hspace{0.05cm}t} $$
 
:$$\Rightarrow \hspace{0.3cm}h_1(t) =    2 \cdot \frac {-1 + {\rm j}\cdot 2 +2.5} {(-1 + {\rm j}\cdot 2) - (-1 - {\rm j}\cdot 2)}\cdot  {\rm e}^{\hspace{0.05cm}p_{\rm x 1}
 
:$$\Rightarrow \hspace{0.3cm}h_1(t) =    2 \cdot \frac {-1 + {\rm j}\cdot 2 +2.5} {(-1 + {\rm j}\cdot 2) - (-1 - {\rm j}\cdot 2)}\cdot  {\rm e}^{\hspace{0.05cm}p_{\rm x 1}
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:$$\Rightarrow \hspace{0.3cm}h_2(t) =2 \cdot \frac {1.5 - {\rm j}\cdot 2} {-{\rm j}\cdot 4}\cdot  {\rm e}^{\hspace{0.05cm}p_{\rm x 2} \hspace{0.03cm}\cdot\hspace{0.05cm}t}= (1 + {\rm j}\cdot 0.75)\cdot {\rm e}^{-t}\cdot {\rm  e}^{\hspace{0.03cm}-{\rm j}\hspace{0.05cm}\cdot \hspace{0.05cm} 2t} \hspace{0.05cm} . $$
 
:$$\Rightarrow \hspace{0.3cm}h_2(t) =2 \cdot \frac {1.5 - {\rm j}\cdot 2} {-{\rm j}\cdot 4}\cdot  {\rm e}^{\hspace{0.05cm}p_{\rm x 2} \hspace{0.03cm}\cdot\hspace{0.05cm}t}= (1 + {\rm j}\cdot 0.75)\cdot {\rm e}^{-t}\cdot {\rm  e}^{\hspace{0.03cm}-{\rm j}\hspace{0.05cm}\cdot \hspace{0.05cm} 2t} \hspace{0.05cm} . $$
  
Using&nbsp; [[Signal_Representation/Calculating_With_Complex_Numbers#Representation_by_magnitude_and_phase|Euler's theorem]]&nbsp; the following is obtained for the sum signal:
+
Using&nbsp; [[Signal_Representation/Calculating_With_Complex_Numbers#Representation_by_magnitude_and_phase|&raquo;Euler's theorem&laquo;]]&nbsp; the following is obtained for the sum signal:
 
:$$h(t) =  h_1(t) + h_2(t)\hspace{0.3cm}  
 
:$$h(t) =  h_1(t) + h_2(t)\hspace{0.3cm}  
 
\Rightarrow \hspace{0.3cm}h(t) = {\rm  e}^{-t}\cdot \big [ (1 - {\rm j}\cdot 0.75)\cdot (\cos() + {\rm j}\cdot \sin())+
 
\Rightarrow \hspace{0.3cm}h(t) = {\rm  e}^{-t}\cdot \big [ (1 - {\rm j}\cdot 0.75)\cdot (\cos() + {\rm j}\cdot \sin())+
Line 133: Line 147:
  
  
==Critically-damped case==
+
==Critically attenuated case==
'''KORREKTUR: attenuated'''
 
 
<br>
 
<br>
With &nbsp;$R = 50 \ \rm Ω$, &nbsp;$L = 25 \ \rm &micro; H$&nbsp; and&nbsp; &nbsp;$C = 40 \ \rm nF$&nbsp; we get the so-called "critically-damped '''KORREKTUR: attenuated''' case":
+
With &nbsp;$R = 50 \ \rm Ω$, &nbsp;$L = 25 \ \rm &micro; H$&nbsp; and&nbsp; &nbsp;$C = 40 \ \rm nF$&nbsp; we get the so-called&nbsp; &raquo;critically attenuated case&laquo;:
 
:$$H_{\rm L}(p)= K \cdot \frac {p - p_{\rm o }} {(p - p_{\rm x })^2}= 2 \cdot \frac {p + 0.5 } {(p +1)^2}  \hspace{0.05cm} .$$
 
:$$H_{\rm L}(p)= K \cdot \frac {p - p_{\rm o }} {(p - p_{\rm x })^2}= 2 \cdot \frac {p + 0.5 } {(p +1)^2}  \hspace{0.05cm} .$$
  
The capacitance value &nbsp;$C = 40 \ \rm nF$&nbsp; is the smallest possible value for which there are just real pole places.&nbsp;
+
The capacitance &nbsp;$C = 40 \ \rm nF$&nbsp; is the smallest possible value for which there are just real pole places.&nbsp; These coincide,&nbsp; that &nbsp;$p_{\rm x} = \ -1$&nbsp; is a double pole place.&nbsp; The time function is thus according to the residue theorem with &nbsp;$l = 2$:
 
 
These coincide, that is &nbsp;$p_{\rm x} = \ -1$&nbsp; is a double pole place.&nbsp; The time function is thus according to the residue theorem with &nbsp;$l = 2$:
 
 
:$$h(t) = {\rm Res} \bigg |_{p \hspace{0.05cm}= \hspace{0.05cm}p_{ {\rm x} } } \hspace{-0.7cm}\{H_{\rm L}(p)\cdot {\rm e}^{p t}\}= \frac{ {\rm d} }{ {\rm d}p}\hspace{0.15cm}
 
:$$h(t) = {\rm Res} \bigg |_{p \hspace{0.05cm}= \hspace{0.05cm}p_{ {\rm x} } } \hspace{-0.7cm}\{H_{\rm L}(p)\cdot {\rm e}^{p t}\}= \frac{ {\rm d} }{ {\rm d}p}\hspace{0.15cm}
 
  \left \{H_{\rm L}(p)\cdot (p - p_{ {\rm x} })^2\cdot {\rm e}^{p \hspace{0.05cm}t}\right\} \bigg |_{p \hspace{0.05cm}= \hspace{0.05cm}p_{ {\rm x} } } = K \cdot \frac{ {\rm d} }{ {\rm d}p}\hspace{0.15cm}\left \{ (p - p_{ {\rm o} })\cdot {\rm e}^{p \hspace{0.05cm}t}\right\}  \bigg |_{p \hspace{0.05cm}= \hspace{0.05cm}p_{ {\rm x} } } \hspace{0.05cm} .$$
 
  \left \{H_{\rm L}(p)\cdot (p - p_{ {\rm x} })^2\cdot {\rm e}^{p \hspace{0.05cm}t}\right\} \bigg |_{p \hspace{0.05cm}= \hspace{0.05cm}p_{ {\rm x} } } = K \cdot \frac{ {\rm d} }{ {\rm d}p}\hspace{0.15cm}\left \{ (p - p_{ {\rm o} })\cdot {\rm e}^{p \hspace{0.05cm}t}\right\}  \bigg |_{p \hspace{0.05cm}= \hspace{0.05cm}p_{ {\rm x} } } \hspace{0.05cm} .$$
  
[[File:EN_LZI_T_3_3_S3c.png |right|frame| Impulse response and step response of the critically-damped '''KORREKTUR: attenuated''' case]]
+
[[File:EN_LZI_T_3_3_S3c.png |right|frame| Impulse response and step response of the critically attenuated case]]
Using the&nbsp; "product rule"&nbsp; of differential calculus, this gives:
+
Using the&nbsp; &raquo;product rule&laquo;&nbsp; of differential calculus,&nbsp; this gives:
 
:$$h(t) = K \cdot \left [ {\rm e}^{p \hspace{0.05cm}t} + (p - p_{ {\rm o} })\cdot t \cdot {\rm e}^{p \hspace{0.05cm}t} \right ] \bigg |_{p \hspace{0.05cm}= \hspace{0.05cm}-1} = {\rm  e}^{-t}\cdot \left ( 2 - t \right)
 
:$$h(t) = K \cdot \left [ {\rm e}^{p \hspace{0.05cm}t} + (p - p_{ {\rm o} })\cdot t \cdot {\rm e}^{p \hspace{0.05cm}t} \right ] \bigg |_{p \hspace{0.05cm}= \hspace{0.05cm}-1} = {\rm  e}^{-t}\cdot \left ( 2 - t \right)
 
  \hspace{0.05cm} .$$
 
  \hspace{0.05cm} .$$
  
The graph shows this impulse response (green curve) in normalized representation.&nbsp; It differs only slightly from the one with the two different poles at&nbsp; $-0.4$&nbsp; and&nbsp; $-1.6$&nbsp;.  
+
The graph shows this impulse response&nbsp; $($green curve$)$&nbsp; in normalized representation.&nbsp; It differs only slightly from the one with two different poles at&nbsp; $-0.4$&nbsp; and&nbsp; $-1.6$&nbsp;.  
  
The signal drawn in red &nbsp; &rArr; &nbsp; $y(t) = 1 - {\rm e}^{-t} + t \cdot {\rm e}^{-t}$&nbsp; results when a step function is also considered at the input &nbsp; &rArr; &nbsp; "step response".  
+
The signal drawn in red &nbsp; &rArr; &nbsp; $y(t) = 1 - {\rm e}^{-t} + t \cdot {\rm e}^{-t}$&nbsp; results when a step function&nbsp; $\gamma(t)$&nbsp; is considered at the input &nbsp; &rArr; &nbsp; &raquo;step response&laquo;.  
  
 
To calculate the step response &nbsp;$\sigma(t) = y(t)$&nbsp; one can alternatively  
 
To calculate the step response &nbsp;$\sigma(t) = y(t)$&nbsp; one can alternatively  
*consider an additional pole at &nbsp;$p = 0$ &nbsp; in the residual calculation (marked in red), or
+
*consider the additional red pole at &nbsp;$p = 0$ &nbsp; in the residual calculation,&nbsp;
*form the integral over the impulse response &nbsp;$h(t)$.
+
 
 +
*or form the integral over the impulse response &nbsp;$h(t)$.
  
  
Line 163: Line 175:
 
Prerequisite for the application of the residue theorem is that there are less zeros than poles &nbsp; &rArr; &nbsp; $Z$&nbsp; must always be smaller than &nbsp;$N$&nbsp;.
 
Prerequisite for the application of the residue theorem is that there are less zeros than poles &nbsp; &rArr; &nbsp; $Z$&nbsp; must always be smaller than &nbsp;$N$&nbsp;.
  
If,&nbsp; on the other hand,&nbsp; as in the case of a high-pass filter &nbsp;$Z = N$,&nbsp; then  
+
*If,&nbsp; on the other hand,&nbsp; as in the case of a high-pass filter &nbsp;$Z = N$,&nbsp; then the limit of the p&ndash;transfer function&nbsp; $H_{\rm L}(p)$&nbsp; for large &nbsp;$p$&nbsp; is not equal to zero,  
*is the limit of the spectral function&nbsp; $H_{\rm L}(p)$&nbsp; for large &nbsp;$p$&nbsp; not equal to zero,  
 
*if the associated time signal &nbsp;$y(t)$&nbsp; also contains a &nbsp;[[Signal_Representation/Direct_Current_Signal_-_Limit_Case_of_a_Periodic_Signal#Dirac_.28delta.29_function_in_frequency_domain|Dirac delta functions]], 
 
*the residue theorem fails and a&nbsp; [https://en.wikipedia.org/wiki/Partial_fraction_decomposition '''Partial fraction decomposition''']&nbsp; must be performed.
 
  
 +
*If the associated time signal &nbsp;$y(t)$&nbsp; also contains &nbsp;[[Signal_Representation/Direct_Current_Signal_-_Limit_Case_of_a_Periodic_Signal#Dirac_.28delta.29_function_in_frequency_domain|&raquo;Dirac delta functions&laquo;]],&nbsp;  the residue theorem fails and a&nbsp; [https://en.wikipedia.org/wiki/Partial_fraction_decomposition&nbsp; &raquo;'''partial fraction decomposition'''&laquo;]&nbsp; must be performed.
  
The procedure is to be clarified exemplarily for a high pass of first order.
 
  
[[File:P_ID1775__LZI_T_3_3_S5_neu.png |right|frame| Impulse response of low-pass (blue) and high-pass (red)]]
+
The procedure is to be clarified exemplarily for a high-pass of first order.
 +
 
 
{{GraueBox|TEXT=   
 
{{GraueBox|TEXT=   
 
$\text{Example 1:}$&nbsp;
 
$\text{Example 1:}$&nbsp;
The&nbsp; $p$-transfer function of a&nbsp; "first-order RC high-pass filter"&nbsp; can be transformed by splitting off a constant as follows:
+
The&nbsp; $p$-transfer function of a&nbsp; &raquo;first-order RC high-pass filter&laquo;&nbsp; can be transformed by splitting off a constant as follows:
 +
[[File:EN_LZI_T_3_3_S5_v2.png |right|frame| Impulse response of low-pass&nbsp; $($blue$)$&nbsp; and high-pass&nbsp; $($red$)$]]
 
:$$\frac{p}{p + RC} = 1- \frac{RC}{p + RC}\hspace{0.05cm} .$$
 
:$$\frac{p}{p + RC} = 1- \frac{RC}{p + RC}\hspace{0.05cm} .$$
Thus, the high-pass impulse response is:
+
Thus,&nbsp; the high-pass impulse response is:
 
:$$h_{\rm HP}(t) = \delta(t) - h_{\rm TP}(t) \hspace{0.05cm} .$$
 
:$$h_{\rm HP}(t) = \delta(t) - h_{\rm TP}(t) \hspace{0.05cm} .$$
  
 
The graph shows  
 
The graph shows  
*as a red curve the high pass&ndash;impulse response &nbsp;$h_{\rm HP}(t)$,
+
*as blue curve the impulse response &nbsp;$h_{\rm TP}(t)$&nbsp; of the equivalent low-pass,  
*as a blue curve the impulse response &nbsp;$h_{\rm TP}(t)$&nbsp; of the equivalent low pass.  
+
 
 +
*as red curve the high&ndash;pass impulse response &nbsp;$h_{\rm HP}(t)$.
  
  
The Dirac delta function is the Laplace transform of the constant value&nbsp; $1$,&nbsp; <br>while the second function to be subtracted gives the impulse response of the equivalent low-pass filter, which is given by  the residue theorem with &nbsp;
+
&rArr; &nbsp; The Dirac delta function is the Laplace transform of the constant value&nbsp; $1$,&nbsp; <br>while the second function to be subtracted gives the impulse response of the equivalent low-pass filter,&nbsp; which is given by  the residue theorem with &nbsp;
 
:$$Z = 0,\hspace{0.2cm} N =1,\hspace{0.2cm} K = RC.$$ }}
 
:$$Z = 0,\hspace{0.2cm} N =1,\hspace{0.2cm} K = RC.$$ }}
  

Latest revision as of 16:03, 21 November 2023

Problem formulation and prerequisites


$\text{Task:}$  This chapter deals with the following problem:

  • The  $p$–spectral function  $Y_{\rm L}(p)$  is given in  »pole-zero notation«.
  • The  »inverse Laplace transform«, i.e. the associated time function  $y(t)$  is searched-for,  where the following notation should hold:
$$y(t) = {\rm L}^{-1}\{Y_{\rm L}(p)\}\hspace{0.05cm} , \hspace{0.3cm}{\rm briefly}\hspace{0.3cm} y(t) \quad \circ\!\!-\!\!\!-^{\hspace{-0.25cm}\rm L}\!\!\!-\!\!\bullet\quad Y_{\rm L}(p)\hspace{0.05cm} .$$
Prerequisites for the chapter "Inverse Laplace Transform"


The graph summarizes the prerequisites for this task.

  • $H_{\rm L}(p)$  describes the transfer function of the causal system and  $Y_{\rm L}(p)$  specifies the Laplace transform of the output signal  $y(t)$  considering the input signal  $x(t)$ .  $Y_{\rm L}(p)$  is characterized by  $N$  poles,  by  $Z ≤ N$  zeros and by the constant  $K.$
  • Poles and zeros exhibit the properties mentioned in the  »last chapter«:  Poles are only allowed in the left  $p$–half plane or on the imaginary axis;  zeros are also allowed in the right  $p$–half plane.
  • All  »singularities«  – this is the generic term for poles and zeros – are either real or exist as pairs of conjugate-complex singularities.  Multiple poles and zeros are also allowed.
  • With the input  $x(t) = δ(t)$   ⇒   $X_{\rm L}(p) = 1$   ⇒   $Y_{\rm L}(p) = H_{\rm L}(p)$, the output signal  $y(t)$  then describes the »impulse response«  $h(t)$  of the transmission system.  For this purpose,  only the singularities drawn in green in the graph may be used for computation.
  • A unit jump function  $x(t) = γ(t)$   ⇒   $ X_{\rm L} = 1/p$  at the input causes the output signal  $y(t)$  to be equal to the  »step response«   $σ(t)$ of $H_{\rm L}(p)$ .  In addition to the singularities of  $H_{\rm L}(p)$,  the pole  $($shown in red in the graph$)$  at  $p = 0$  must now also be taken into account for computation.
  • Possible as input  $x(t)$  are only signals for which  $X_{ \rm L}(p)$  can be expressed in pole-zero notation  (see the  $\text{table}$  in the chapter »Laplace Transform and $p$–Transfer Function»$)$,  for example a cosine or sine signal switched on at time  $t = 0$ .
  • So,  a rectangular signal  $x(t)\ \ ⇒ \ \ X_{\rm L}(p) = (1 - {\rm e}^{\hspace{0.05cm}p\hspace{0.05cm}\cdot \hspace{0.05cm} T})/p$  is not possible in the approach described here.  However, the rectangular response  $y(t)$  can be computed indirectly as the difference of two step responses.

Some results of function theory


In contrast to the  »Fourier integrals«,  which differ only slightly in the two directions of transformation,  for  »Laplace«  the computation of  $y(t)$  from  $Y_{\rm L}(p)$ – that is the inverse transformation – is

  • much more difficult than computing  $Y_{\rm L}(p)$  from  $y(t)$,
  • unresolvable or solvable only very laboriously by elementary means.


$\text{Definition:}$  In general, the following holds for the  »inverse Laplace transform«:

$$y(t) = {\rm L}^{-1}\{Y_{\rm L}(p)\}= \lim_{\beta \hspace{0.05cm}\rightarrow \hspace{0.05cm}\infty} \hspace{0.15cm} \frac{1}{ {\rm j} \cdot 2 \pi}\cdot \int_{ \alpha - {\rm j} \hspace{0.05cm}\cdot \hspace{0.05cm}2 \pi \beta } ^{\alpha+{\rm j} \hspace{0.05cm}\cdot \hspace{0.05cm}2 \pi \beta} Y_{\rm L}(p) \hspace{0.05cm}\cdot \hspace{0.05cm} {\rm e}^{\hspace{0.05cm}p \hspace{0.05cm}\cdot \hspace{0.05cm} t}\hspace{0.1cm}{\rm d}p \hspace{0.05cm} .$$
  1. The integration is parallel to the imaginary axis.
  2. The real part  $α$  is to be chosen such that all poles are located to the left of the integration path.


The left graph illustrates this line integral along the red dotted vertical  ${\rm Re}\{p\}= α$.  This integral is solvable using  »Jordan's lemma of complex analysis«.  In this tutorial only a very short and simple summary of the approach is depicted:

Line integral together with left and right circular integral
  1. The line integral can be divided into two circular integrals so that all poles are located in the left circular integral while the right circular integral may only contain zeros.
  2. According to the theory of functions, the right circular integral yields the time function  $y(t)$  for negative times. 
  3. Due to causality,  $y(t < 0)$  must be identical to zero,  but according to the fundamentals of function theorem this is only true if there are no poles in the right  $p$–half-plane.
  4. In contrast,  the integral over the left semicircle yields the time function for  $t ≥ 0$. 
  5. This encloses all poles and can be computed using the  »residue theorem«  in a  $($relatively$)$  simple way,  as it will be shown in the next sections.


Formulation of the residue theorem


It is further assumed that the transfer function  $Y_{\rm L}(p)$  can be expressed in pole-zero notation by

  • the constant factor  $K$,
  • the  $Z$  »zeros«  $p_{{\rm o}i}$  $(i = 1$, ... , $Z)$  and
  • the  $N$  »poles«  $p_{{\rm x}i}$  $(i = 1$, ... , $N$).


We also assume  $Z < N$.  The number of  »distinguishable poles«  is denoted by  $I$.  Multiple poles are counted only once to determine  $I$.  Thus,  the following holds for the  $\text{sketch}$  in the last section considering the double pole:  

$$N = 5,\hspace{0.3cm} I = 4.$$

$\text{Residue Theorem:}$  Considering the above conditions,  the  »inverse Laplace transform«  of  $Y_{\rm L}(p)$  for times  $t ≥ 0$  is obtained as the sum of  $I$  natural oscillations of the poles,  which are called the  »residuals«  – abbreviated as  $\rm Res$:

$$y(t) = \sum_{i=1}^{I}{\rm Res} \bigg \vert _{p \hspace{0.05cm}= \hspace{0.05cm}p_{{\rm x}_i}} \hspace{-0.7cm}\{Y_{\rm L}(p)\cdot {\rm e}^{p \hspace{0.05cm}t}\} \hspace{0.05cm} .$$

Since  $Y_{\rm L}(p)$  is only specifiable for causal signals,  $y(t < 0) = 0$  always holds for negative times.

  • In general,  the following holds for a pole of multiplicity  $l$ :
$${\rm Res} \bigg \vert _{p \hspace{0.05cm}= \hspace{0.05cm}p_{ {\rm x}_i} } \hspace{-0.7cm}\{Y_{\rm L}(p)\cdot {\rm e}^{p t}\}= \frac{1}{(l-1)!}\cdot \frac{ {\rm d}^{\hspace{0.05cm}l-1} }{ {\rm d}p^{\hspace{0.05cm}l-1} }\hspace{0.15cm} \left \{Y_{\rm L}(p)\cdot (p - p_{ {\rm x}_i})^{\hspace{0.05cm}l}\cdot {\rm e}^{p \hspace{0.05cm}t}\right\} \bigg \vert_{p \hspace{0.05cm}= \hspace{0.05cm}p_{ {\rm x}_i} } \hspace{0.05cm} .$$
  • The following is obtained out of it with  $l = 1$  for a simple pole as a special case:
$${\rm Res} \bigg\vert_{p \hspace{0.05cm}= \hspace{0.05cm}p_{ {\rm x}_i} } \hspace{-0.7cm}\{Y_{\rm L}(p)\cdot {\rm e}^{p t}\}= Y_{\rm L}(p)\cdot (p - p_{ {\rm x}_i} )\cdot {\rm e}^{p \hspace{0.05cm}t} \bigg \vert _{p \hspace{0.05cm}= \hspace{0.05cm}p_{ {\rm x}_i} } \hspace{0.05cm} .$$


In the next sections,  the  »residue theorem«  is illustrated by three detailed examples corresponding to the three constellations in  $\text{Example 3}$  of chapter  »Laplace transform and p-transfer function«:

  • So,  we consider again the two-port network with an inductance  $L = 25 \ \rm µH$  in the longitudinal branch as well as the the series connection of an ohmic resistance  $R = 50 \ \rm Ω$  and a capacitance  $C$  in the transverse branch.
  • For the latter,  we consider three different values,  namely  $C = 62.5 \ \rm nF$,  $C = 8 \ \rm nF$  and  $C = 40 \ \rm nF$.
  • The following is always assumed:  $x(t) = δ(t) \; ⇒ \; X_{\rm L}(p) = 1$   ⇒   $Y_{\rm L}(p) = H_{\rm L}(p)$   ⇒   the output signal  $y(t)$  is equal to the impulse response  $h(t)$.

Aperiodically decaying impulse response


The following is obtained for the  $p$–transfer function computed in the section  »pole-zero representation of circuits«  with the capacitance  $C = 62.5 \ \rm nF$.  The other numerical values are given in the graph below:

Aperiodically decaying impulse response
$$H_{\rm L}(p)= K \cdot \frac {p - p_{\rm o }} {(p - p_{\rm x 1})(p - p_{\rm x 2})}= 2 \cdot \frac {p + 0.32 } {(p +0.4)(p +1.6 )} \hspace{0.05cm} .$$

Note the normalization of  $p$,  $K$ and also of all poles and zeros by the factor  ${\rm 10^6} · 1/\rm s$.

⇒   The impulse response is composed of  $I = N = 2$  natural oscillations. For $t < 0$,  these are equal to zero.

  • The residual of the pole at  $p_{{\rm x}1} =\ –0.4$  yields the following time function:
$$h_1(t) = {\rm Res} \bigg |_{p \hspace{0.05cm}= \hspace{0.05cm}p_{{\rm x}1}} \hspace{-0.7cm}\{H_{\rm L}(p)\cdot {\rm e}^{p t}\}= H_{\rm L}(p)\cdot (p - p_{{\rm x}1})\cdot {\rm e}^{p \hspace{0.05cm}t} \bigg |_{p \hspace{0.05cm}= \hspace{0.05cm}p_{{\rm x}1}}$$
$$\Rightarrow \hspace{0.3cm}h_1(t) = 2 \cdot \frac {p + 0.32 } {p +0.4}\cdot {\rm e}^{p \hspace{0.05cm}t} \bigg |_{p \hspace{0.05cm}= \hspace{0.05cm}-0.4}= - \frac {2 } {15}\cdot {\rm e}^{-0.4 \hspace{0.05cm} t} \hspace{0.05cm}. $$
  • In the same way, the residual of the second pole at  $p_{{\rm x}2} = \ –1.6$  can be computed:
$$h_2(t) = {\rm Res} \bigg |_{p \hspace{0.05cm}= \hspace{0.05cm}p_{{\rm x}2}} \hspace{-0.7cm}\{H_{\rm L}(p)\cdot {\rm e}^{p t}\}= H_{\rm L}(p)\cdot (p - p_{{\rm x}2})\cdot {\rm e}^{p \hspace{0.05cm}t} \bigg |_{p \hspace{0.05cm}= \hspace{0.05cm}p_{{\rm x}2}}$$
$$\Rightarrow \hspace{0.3cm}h_2(t) = 2 \cdot \frac {p + 0.32 } {p +1.6}\cdot {\rm e}^{p \hspace{0.05cm}t} \bigg |_{p \hspace{0.05cm}= \hspace{0.05cm}-1.6}= \frac {32 } {15}\cdot {\rm e}^{-1.6 \hspace{0.05cm} t} \hspace{0.05cm}. $$

The graph shows  $h_1(t)$  and  $h_2(t)$  as well as the sum signal  $h(t)$.

  1. The normalization factor  $1/T = 10^6 · \rm 1/s$  is taken into account here so that the time is normalized to  $T = 1 \ \rm µ s$ .
  2. For  $t =0$,  $T \cdot h(t=0) = {32 }/ {15} -{2 }/ {15}= 2 \hspace{0.05cm}$  is obtained as a result.
  3. For times  $t > 2 \ \rm µ s$,  the impulse response is negative  $($although only slightly and difficult to see in the graph$)$.


Attenuated-oscillatory impulse response


The component values  $R = 50 \ \rm Ω$,  $L = 25 \ \rm µ H$  and  $C = 8 \ \rm nF$ result in two conjugate complex poles at  $p_{{\rm x}1} = \ –1 + {\rm j} · 2$  and  $p_{{\rm x}2} = \ –1 - {\rm j} · 2$. 

Attenuated-oscillatory impulse response
  • The zero is located at  $p_{\rm o} = \ –2.5$.
  • $K = 2$  holds
  • All numerical values are to be multiplied by factor  $1/T$  $(T = 1\ \rm µ s$).


Applying the residue theorem to this configuration then it is obtained:

$$h_1(t) = K \cdot \frac {p_{\rm x 1} - p_{\rm o }} {p_{\rm x 1} - p_{\rm x 2}} \cdot {\rm e}^{\hspace{0.05cm}p_{\rm x 1} \cdot \hspace{0.05cm}t} $$
$$\Rightarrow \hspace{0.3cm}h_1(t) = 2 \cdot \frac {-1 + {\rm j}\cdot 2 +2.5} {(-1 + {\rm j}\cdot 2) - (-1 - {\rm j}\cdot 2)}\cdot {\rm e}^{\hspace{0.05cm}p_{\rm x 1} \cdot\hspace{0.05cm}t}$$
$$\Rightarrow \hspace{0.3cm}h_1(t) = 2 \cdot \frac {1.5 + {\rm j}\cdot 2} {{\rm j}\cdot 4}\cdot {\rm e}^{\hspace{0.05cm}p_{\rm x 1} \cdot\hspace{0.05cm}t}= (1 - {\rm j}\cdot 0.75)\cdot {\rm e}^{-t}\cdot {\rm e}^{\hspace{0.03cm}{\rm j}\hspace{0.05cm}\cdot \hspace{0.05cm} 2t} \hspace{0.05cm} ,$$
$$ h_2(t) = K \cdot \frac {p_{\rm x 2} - p_{\rm o }} {p_{\rm x 2} - p_{\rm x 1}}\cdot {\rm e}^{\hspace{0.05cm}p_{\rm x 2} \hspace{0.03cm}\cdot \hspace{0.05cm}t} $$
$$\Rightarrow \hspace{0.3cm} h_2(t) = 2 \cdot \frac {-1 - {\rm j}\cdot 2 +2.5} {(-1 - {\rm j}\cdot 2) - (-1 + {\rm j}\cdot 2)}\cdot {\rm e}^{\hspace{0.05cm}p_{\rm x 2} \hspace{0.03cm}\cdot\hspace{0.05cm}t} $$
$$\Rightarrow \hspace{0.3cm}h_2(t) =2 \cdot \frac {1.5 - {\rm j}\cdot 2} {-{\rm j}\cdot 4}\cdot {\rm e}^{\hspace{0.05cm}p_{\rm x 2} \hspace{0.03cm}\cdot\hspace{0.05cm}t}= (1 + {\rm j}\cdot 0.75)\cdot {\rm e}^{-t}\cdot {\rm e}^{\hspace{0.03cm}-{\rm j}\hspace{0.05cm}\cdot \hspace{0.05cm} 2t} \hspace{0.05cm} . $$

Using  »Euler's theorem«  the following is obtained for the sum signal:

$$h(t) = h_1(t) + h_2(t)\hspace{0.3cm} \Rightarrow \hspace{0.3cm}h(t) = {\rm e}^{-t}\cdot \big [ (1 - {\rm j}\cdot 0.75)\cdot (\cos() + {\rm j}\cdot \sin())+ + (1 + {\rm j}\cdot 0.75)\cdot (\cos() - {\rm j}\cdot \sin())\big ]$$
$$\Rightarrow \hspace{0.3cm}h(t) ={\rm e}^{-t}\cdot \big [ 2\cdot \cos(2t) + 1.5 \cdot \sin(2t)\big ]\hspace{0.05cm} . $$

The graph shows the attenuated-oscillatory impulse response  $h(t)$  attenuated by  ${\rm e}^{–t}$  for this pole–zero configuration.


Critically attenuated case


With  $R = 50 \ \rm Ω$,  $L = 25 \ \rm µ H$  and   $C = 40 \ \rm nF$  we get the so-called  »critically attenuated case«:

$$H_{\rm L}(p)= K \cdot \frac {p - p_{\rm o }} {(p - p_{\rm x })^2}= 2 \cdot \frac {p + 0.5 } {(p +1)^2} \hspace{0.05cm} .$$

The capacitance  $C = 40 \ \rm nF$  is the smallest possible value for which there are just real pole places.  These coincide,  that  $p_{\rm x} = \ -1$  is a double pole place.  The time function is thus according to the residue theorem with  $l = 2$:

$$h(t) = {\rm Res} \bigg |_{p \hspace{0.05cm}= \hspace{0.05cm}p_{ {\rm x} } } \hspace{-0.7cm}\{H_{\rm L}(p)\cdot {\rm e}^{p t}\}= \frac{ {\rm d} }{ {\rm d}p}\hspace{0.15cm} \left \{H_{\rm L}(p)\cdot (p - p_{ {\rm x} })^2\cdot {\rm e}^{p \hspace{0.05cm}t}\right\} \bigg |_{p \hspace{0.05cm}= \hspace{0.05cm}p_{ {\rm x} } } = K \cdot \frac{ {\rm d} }{ {\rm d}p}\hspace{0.15cm}\left \{ (p - p_{ {\rm o} })\cdot {\rm e}^{p \hspace{0.05cm}t}\right\} \bigg |_{p \hspace{0.05cm}= \hspace{0.05cm}p_{ {\rm x} } } \hspace{0.05cm} .$$
Impulse response and step response of the critically attenuated case

Using the  »product rule«  of differential calculus,  this gives:

$$h(t) = K \cdot \left [ {\rm e}^{p \hspace{0.05cm}t} + (p - p_{ {\rm o} })\cdot t \cdot {\rm e}^{p \hspace{0.05cm}t} \right ] \bigg |_{p \hspace{0.05cm}= \hspace{0.05cm}-1} = {\rm e}^{-t}\cdot \left ( 2 - t \right) \hspace{0.05cm} .$$

The graph shows this impulse response  $($green curve$)$  in normalized representation.  It differs only slightly from the one with two different poles at  $-0.4$  and  $-1.6$ .

The signal drawn in red   ⇒   $y(t) = 1 - {\rm e}^{-t} + t \cdot {\rm e}^{-t}$  results when a step function  $\gamma(t)$  is considered at the input   ⇒   »step response«.

To calculate the step response  $\sigma(t) = y(t)$  one can alternatively

  • consider the additional red pole at  $p = 0$   in the residual calculation, 
  • or form the integral over the impulse response  $h(t)$.


Partial fraction decomposition


Prerequisite for the application of the residue theorem is that there are less zeros than poles   ⇒   $Z$  must always be smaller than  $N$ .

  • If,  on the other hand,  as in the case of a high-pass filter  $Z = N$,  then the limit of the p–transfer function  $H_{\rm L}(p)$  for large  $p$  is not equal to zero,


The procedure is to be clarified exemplarily for a high-pass of first order.

$\text{Example 1:}$  The  $p$-transfer function of a  »first-order RC high-pass filter«  can be transformed by splitting off a constant as follows:

Impulse response of low-pass  $($blue$)$  and high-pass  $($red$)$
$$\frac{p}{p + RC} = 1- \frac{RC}{p + RC}\hspace{0.05cm} .$$

Thus,  the high-pass impulse response is:

$$h_{\rm HP}(t) = \delta(t) - h_{\rm TP}(t) \hspace{0.05cm} .$$

The graph shows

  • as blue curve the impulse response  $h_{\rm TP}(t)$  of the equivalent low-pass,
  • as red curve the high–pass impulse response  $h_{\rm HP}(t)$.


⇒   The Dirac delta function is the Laplace transform of the constant value  $1$, 
while the second function to be subtracted gives the impulse response of the equivalent low-pass filter,  which is given by the residue theorem with  

$$Z = 0,\hspace{0.2cm} N =1,\hspace{0.2cm} K = RC.$$


Exercises for the chapter

Exercise 3.5: Circuit with R, L and C

Exercise 3.5Z: Application of the Residue Theorem

Exercise 3.6: Transient Behavior

Exercise 3.6Z: Two Imaginary Poles

Exercise 3.7: Impulse Response of a High-Pass Filter

Exercise 3.7Z: Partial Fraction Decomposition