Difference between revisions of "Aufgaben:Exercise 3.8: Triple Convolution?"

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:$$h( t ) = \frac{1}{T}\cdot \left( {1 - \frac{t}{ {2T}}} \right).$$
 
:$$h( t ) = \frac{1}{T}\cdot \left( {1 - \frac{t}{ {2T}}} \right).$$
  
Outside this interval,  $h(t) = 0$. The corresponding spectral function is:
+
Outside this interval,  $h(t) = 0$.  The corresponding spectral function is:
 
   
 
   
 
:$$H( f ) = \frac{1}{ {8\left( {{\rm{\pi }}fT} \right)^2 }} \cdot \left( {1 - {\rm{j \cdot 4\pi }}fT - {\rm{e}}^{ - {\rm{j \hspace{0.05cm}\cdot \hspace{0.05cm} 4\pi }}\hspace{0.05cm}f\hspace{0.05cm}T} } \right).$$
 
:$$H( f ) = \frac{1}{ {8\left( {{\rm{\pi }}fT} \right)^2 }} \cdot \left( {1 - {\rm{j \cdot 4\pi }}fT - {\rm{e}}^{ - {\rm{j \hspace{0.05cm}\cdot \hspace{0.05cm} 4\pi }}\hspace{0.05cm}f\hspace{0.05cm}T} } \right).$$
  
This equation is not suitable for calculating the so-called „equal signal transfer factor”   ⇒    $H(f = 0)$ , since both the bracket expression and the denominator become zero. However, it is also valid:
+
This equation is not suitable for calculating the so-called  "direct signal transfer factor"   ⇒    $H(f = 0)$,  since both the bracket expression and the denominator become zero.  However, it is also valid:
 
   
 
   
 
:$$H( {f = 0} ) = \int_0^{2T} {h( t )\hspace{0.1cm}{\rm d}t = 1.}$$
 
:$$H( {f = 0} ) = \int_0^{2T} {h( t )\hspace{0.1cm}{\rm d}t = 1.}$$
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Three different time signals are applied to the input of this filter (see sketch):
 
Three different time signals are applied to the input of this filter (see sketch):
 
* $x_1(t)$  is a DC signal with height  $x_0 = 1 \hspace{0.05cm}{\rm V}$.
 
* $x_1(t)$  is a DC signal with height  $x_0 = 1 \hspace{0.05cm}{\rm V}$.
* $x_2(t)$  is a square-wave pulse with duration  $T$  and height  $x_0 = 1\hspace{0.05cm} {\rm V}$, starting at  $t = T$.
+
* $x_2(t)$  is a rectangular pulse with duration  $T$  and height  $x_0 = 1\hspace{0.05cm} {\rm V}$, starting at  $t = T$.
 
* $x_3(t)$  is a cosine signal with frequency  $f_0 = 3/T$  and amplitude  $x_0 = 1 \hspace{0.05cm}{\rm V}$.
 
* $x_3(t)$  is a cosine signal with frequency  $f_0 = 3/T$  and amplitude  $x_0 = 1 \hspace{0.05cm}{\rm V}$.
  
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''Hints:''  
 
''Hints:''  
 
*This exercise belongs to the chapter  [[Signal_Representation/The_Convolution_Theorem_and_Operation|The Convolution Theorem and Operation]].
 
*This exercise belongs to the chapter  [[Signal_Representation/The_Convolution_Theorem_and_Operation|The Convolution Theorem and Operation]].
*The topic of this section is also illustrated in the  [[Applets:Zur_Verdeutlichung_der_grafischen_Faltung|To Illustrate the Graphical Convolution]]  veranschaulicht.
+
*The topic of this section is also illustrated in the interactive applet  [[Applets:Graphical_Convolution| Graphical Convolution]].
 
   
 
   
  
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- $y_3(t) = x_3(t) \ast h(t)$.
 
- $y_3(t) = x_3(t) \ast h(t)$.
  
{What is the signal  $y_1(t)$  at the filter output when the DC signal  $x_1(t) = 1 \hspace{0.03cm}{\rm V}$  is applied to the input? Give the signal value at  $t = 2T$ .
+
{What is the signal  $y_1(t)$  at the filter output when the DC signal  $x_1(t) = 1 \hspace{0.03cm}{\rm V}$  is applied to the input?  Give the signal value at  $t = 2T$.
 
|type="{}"}
 
|type="{}"}
 
$y_1(t=2T)\ = \ $  { 1 3% }  ${\rm V}$  
 
$y_1(t=2T)\ = \ $  { 1 3% }  ${\rm V}$  
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$y_2(t=3T)\ = \ $ { 0.25 3%  }  ${\rm V}$  
 
$y_2(t=3T)\ = \ $ { 0.25 3%  }  ${\rm V}$  
  
{What is the output signal  $y_3(t)$, when the cosine signal  $x_3(t)$  is applied to the input? Give the signal value at  $t =0$  an.
+
{What is the output signal  $y_3(t)$, when the cosine signal  $x_3(t)$  is applied to the input?  Give the signal value at  $t =0$.
 
|type="{}"}
 
|type="{}"}
 
$y_3(t=0)\ = \ $ { 0. }  ${\rm V}$
 
$y_3(t=0)\ = \ $ { 0. }  ${\rm V}$
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{{ML-Kopf}}
 
{{ML-Kopf}}
 
'''(1)'''&nbsp; The correct <u>answer is 2</u>:
 
'''(1)'''&nbsp; The correct <u>answer is 2</u>:
*$x_1(t)$&nbsp; and&nbsp; $x_3(t)$&nbsp; each contain only one frequency, namely&nbsp; $f = 0$&nbsp; or&nbsp; $f = f_0$ . In each case, the diversions via the spectrum is preferable.  
+
*Both&nbsp; $x_1(t)$&nbsp; and&nbsp; $x_3(t)$&nbsp; contain only one frequency, namely&nbsp; $f = 0$&nbsp; or&nbsp; $f = f_0$.&nbsp; In each case, the diversions via the spectrum is preferable.  
*Beim Rechtecksignal&nbsp; $x_2(t)$&nbsp; the calculation via convolution is more favourable, since the Fourier back transformation of&nbsp; $Y_2(f)$&nbsp; is complicated.
+
*With the rectangular pulse&nbsp; $x_2(t)$&nbsp; the calculation via convolution is more favourable, since the inverse Fourier transform of&nbsp; $Y_2(f)$&nbsp; is complicated.
  
  
'''(2)'''&nbsp; For the square wave signal&nbsp; $x_1(t)$&nbsp; the output signal is also a DC signal, since the following equations apply:
+
'''(2)'''&nbsp; For the signal&nbsp; $x_1(t)$&nbsp; the output signal is also a DC signal, since the following equations apply:
 
   
 
   
:$$Y_1 (f) = X_1 (f) \cdot H(f)\quad {\rm{mit}}\quad X_1 (f) = 1\;{\rm{V}} \cdot \delta (f)$$
+
:$$Y_1 (f) = X_1 (f) \cdot H(f)\quad {\rm{with}}\quad X_1 (f) = 1\;{\rm{V}} \cdot \delta (f)$$
 
   
 
   
 
:$$ \Rightarrow Y_1 (f) = 1\;{\rm{V}} \cdot \delta (f) \cdot H( {f = 0} ) = 1\;{\rm{V}} \cdot \delta (f) \; \Rightarrow \; y_1 (t) = 1\;{\rm{V}} \cdot H( {f = 0} ) \hspace{0.15 cm}\underline{= 1\;{\rm{V}}}.$$
 
:$$ \Rightarrow Y_1 (f) = 1\;{\rm{V}} \cdot \delta (f) \cdot H( {f = 0} ) = 1\;{\rm{V}} \cdot \delta (f) \; \Rightarrow \; y_1 (t) = 1\;{\rm{V}} \cdot H( {f = 0} ) \hspace{0.15 cm}\underline{= 1\;{\rm{V}}}.$$
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'''(3)'''&nbsp; The mirrored signal&nbsp; $x_2(-t)$&nbsp; has signal components between&nbsp; $-2T$&nbsp; and&nbsp; $-T$.  
 
'''(3)'''&nbsp; The mirrored signal&nbsp; $x_2(-t)$&nbsp; has signal components between&nbsp; $-2T$&nbsp; and&nbsp; $-T$.  
*Only a shift by&nbsp; $T \hspace{-0.1cm}+ \hspace{-0.1cm}\varepsilon$&nbsp; leads to an overlap with&nbsp; $h(t)$. Here&nbsp; $\varepsilon$&nbsp; denotes an arbitrarily small but positive time.
+
*Only a shift by&nbsp; $T \hspace{-0.1cm}+ \hspace{-0.1cm}\varepsilon$&nbsp; leads to an overlap with&nbsp; $h(t)$.&nbsp; Here&nbsp; $\varepsilon$&nbsp; denotes an arbitrarily small but positive time.
  
*However, if the shift is greater than&nbsp; $4T\hspace{-0.1cm} - \hspace{-0.1cm}\varepsilon$, the integration over the product also yields the value zero. From this follows:   
+
*However, if the shift is greater than&nbsp; $4T\hspace{-0.1cm} - \hspace{-0.1cm}\varepsilon$, the integration over the product also yields the value zero.&nbsp; From this follows:   
 
:$$t_{\text{min}} \;\underline{= T},  \ \ \  t_{\text{max}} \;\underline{= 4T}.$$
 
:$$t_{\text{min}} \;\underline{= T},  \ \ \  t_{\text{max}} \;\underline{= 4T}.$$
  
  
[[File:P_ID534__Sig_A_3_8_d.png|right|frame|Convolution rectangle and triangle ]]
+
[[File:P_ID534__Sig_A_3_8_d.png|right|frame|"Rectangle"&nbsp; $\star$&nbsp; "Triangle" ]]
 
'''(4)'''&nbsp; The result of the graphical convolution for the times&nbsp; $t = 2T$&nbsp; and&nbsp; $t = 3T$&nbsp; can be seen in the adjacent sketch.  
 
'''(4)'''&nbsp; The result of the graphical convolution for the times&nbsp; $t = 2T$&nbsp; and&nbsp; $t = 3T$&nbsp; can be seen in the adjacent sketch.  
 
*The value at&nbsp; $t = 2T$&nbsp; corresponds to the area highlighted in red:
 
*The value at&nbsp; $t = 2T$&nbsp; corresponds to the area highlighted in red:
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 +
'''(4a)'''&nbsp; For&nbsp; $T \leq t \leq 2T$&nbsp; the lower&nbsp; $($German:&nbsp; "untere" &nbsp; &rArr; &nbsp; "u"$)$&nbsp; limit is&nbsp; $τ_u = 0$, and the upper&nbsp; $($German:&nbsp; "obere" &nbsp; &rArr; &nbsp; "o"$)$&nbsp; limit is&nbsp; $τ_0 = t - T$:
 
[[File:P_ID583__Sig_A_3_8_d1_neu.png|right|frame|Convolution for&nbsp; $T \leq t \leq 2T$]]
 
[[File:P_ID583__Sig_A_3_8_d1_neu.png|right|frame|Convolution for&nbsp; $T \leq t \leq 2T$]]
'''(4a)'''&nbsp; For&nbsp; $T \leq t \leq 2T$&nbsp; the lower limit is&nbsp; $τ_u = 0$, the upper limit is&nbsp; $τ_0 = t - T$:
 
 
   
 
   
 
:$$y_2 (t) = \int_{\tau _u }^{\tau _0 } {h(\tau )\,{\rm{d}}\tau  = \int_0^{t - T} {\frac{1}{T}} }\cdot  \left( {1 - \frac{\tau }{ {2T}}} \right)\,{\rm{d}}\tau .$$
 
:$$y_2 (t) = \int_{\tau _u }^{\tau _0 } {h(\tau )\,{\rm{d}}\tau  = \int_0^{t - T} {\frac{1}{T}} }\cdot  \left( {1 - \frac{\tau }{ {2T}}} \right)\,{\rm{d}}\tau .$$
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:$$\Rightarrow \hspace{0.3cm}y_2 (t) = 1.5 \cdot {t}/{T} - 0.25\cdot \left( {{t}/{T}} \right)^2  - 1.25.$$
 
:$$\Rightarrow \hspace{0.3cm}y_2 (t) = 1.5 \cdot {t}/{T} - 0.25\cdot \left( {{t}/{T}} \right)^2  - 1.25.$$
 
   
 
   
*For verification we consider the two limits. We get the values&nbsp; $y_2(T) = 0$&nbsp; and&nbsp; $y_2(2T) = 0.75$.
+
*For verification we consider the two limits.&nbsp; We get the values&nbsp; $y_2(T) = 0$&nbsp; and&nbsp; $y_2(2T) = 0.75$.
 
+
<br clear=all>
 
 
 
[[File:P_ID584__Sig_A_3_8_d2_neu.png|right|frame|Convolution for&nbsp; $2T \leq t \leq 3T$]]
 
[[File:P_ID584__Sig_A_3_8_d2_neu.png|right|frame|Convolution for&nbsp; $2T \leq t \leq 3T$]]
'''(4b)'''&nbsp; In the interval&nbsp; $2T \leq t \leq 3T$&nbsp; ,&nbsp; $τ_0 = t - T$, still holds, while now&nbsp; $τ_u = t - 2T$&nbsp;:
+
'''(4b)'''&nbsp; In the interval&nbsp; $2T \leq t \leq 3T$,&nbsp; the lower limit&nbsp; $τ_0 = t - T$&nbsp; still holds, while now&nbsp; $τ_u = t - 2T$:
 
   
 
   
 
::$$y_2 (t) = I(t - T) - I(t - 2T) = 1.75 - 0.5 \cdot {t}/{T}.$$
 
::$$y_2 (t) = I(t - T) - I(t - 2T) = 1.75 - 0.5 \cdot {t}/{T}.$$
  
This corresponds to a linear decrease with the two limit values&nbsp;
+
This corresponds to a linear decrease with the two limit values:
 
:$$y_2(2T) = 0.75,$$
 
:$$y_2(2T) = 0.75,$$
 
:$$y_2(3T) = 0.25.$$
 
:$$y_2(3T) = 0.25.$$
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<br clear=all>
 
<br clear=all>
 
'''(5)'''&nbsp; In principle, this sub-task could also be solved directly with the convolution.
 
'''(5)'''&nbsp; In principle, this sub-task could also be solved directly with the convolution.
*However, since&nbsp; $x_3(t)$&nbsp; is an even function, the reflection can now be dispensed with here and we obtain:  
+
*However, since&nbsp; $x_3(t)$&nbsp; is an even function, the mirror can now be dispensed and we obtain:  
 
   
 
   
 
:$$y_3 (t) = \int_{ - \infty }^{ + \infty } {h(\tau ) \cdot x_3 (t + \tau )\hspace{0.1cm}{\rm{d}}\tau  = x_0 }\cdot \int_0^{2T} {h(\tau ) \cdot \cos (2{\rm{\pi }}f_0 (t + \tau )\hspace{0.1cm}{\rm{d}}\tau .}$$
 
:$$y_3 (t) = \int_{ - \infty }^{ + \infty } {h(\tau ) \cdot x_3 (t + \tau )\hspace{0.1cm}{\rm{d}}\tau  = x_0 }\cdot \int_0^{2T} {h(\tau ) \cdot \cos (2{\rm{\pi }}f_0 (t + \tau )\hspace{0.1cm}{\rm{d}}\tau .}$$
  
*The simpler way here is via the spectra. $X(f)$&nbsp; consists of two diraclines at&nbsp; $\pm 3f_0$. Thus, the frequency response must also only be calculated for this frequency:
+
*The simpler way here is via the spectra.&nbsp; $X(f)$&nbsp; consists of two diraclines at&nbsp; $\pm 3f_0$.&nbsp; Thus, the frequency response must also only be calculated for this frequency:
 
   
 
   
 
:$$H( {f = 3f_0 } ) =  \frac{1}{ {72{\rm{\pi }}^{\rm{2}} }}\big[ {1 - {\rm{j}}\cdot 12{\rm{\pi }} - {\rm{cos}}( {{\rm{12\pi }}} ) + {\rm{j}}\cdot \sin ( {{\rm{12\pi }}})} \big]  =  \frac{1}{ {72{\rm{\pi }}^{\rm{2}} }}\big[ 1 - {\rm j}\cdot 12{\rm \pi } - 1 + {\rm j}\cdot 0 \big]= { - {\rm{j}}} \cdot \frac{1}{ {6{\rm{\pi }}}}.$$
 
:$$H( {f = 3f_0 } ) =  \frac{1}{ {72{\rm{\pi }}^{\rm{2}} }}\big[ {1 - {\rm{j}}\cdot 12{\rm{\pi }} - {\rm{cos}}( {{\rm{12\pi }}} ) + {\rm{j}}\cdot \sin ( {{\rm{12\pi }}})} \big]  =  \frac{1}{ {72{\rm{\pi }}^{\rm{2}} }}\big[ 1 - {\rm j}\cdot 12{\rm \pi } - 1 + {\rm j}\cdot 0 \big]= { - {\rm{j}}} \cdot \frac{1}{ {6{\rm{\pi }}}}.$$
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__NOEDITSECTION__
 
__NOEDITSECTION__
[[Category:Exercises for Signal Representation|^3.4 The Convolution Theorem^]]
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[[Category:Signal Representation: Exercises|^3.4 The Convolution Theorem^]]

Latest revision as of 14:27, 29 April 2021

Impulse response  $h(t)$  and
three input signals  $x(t)$

The impulse response of an LTI system has the following course in the time range between  $0$  and  $2T$ :

$$h( t ) = \frac{1}{T}\cdot \left( {1 - \frac{t}{ {2T}}} \right).$$

Outside this interval,  $h(t) = 0$.  The corresponding spectral function is:

$$H( f ) = \frac{1}{ {8\left( {{\rm{\pi }}fT} \right)^2 }} \cdot \left( {1 - {\rm{j \cdot 4\pi }}fT - {\rm{e}}^{ - {\rm{j \hspace{0.05cm}\cdot \hspace{0.05cm} 4\pi }}\hspace{0.05cm}f\hspace{0.05cm}T} } \right).$$

This equation is not suitable for calculating the so-called  "direct signal transfer factor"   ⇒   $H(f = 0)$,  since both the bracket expression and the denominator become zero.  However, it is also valid:

$$H( {f = 0} ) = \int_0^{2T} {h( t )\hspace{0.1cm}{\rm d}t = 1.}$$

Three different time signals are applied to the input of this filter (see sketch):

  • $x_1(t)$  is a DC signal with height  $x_0 = 1 \hspace{0.05cm}{\rm V}$.
  • $x_2(t)$  is a rectangular pulse with duration  $T$  and height  $x_0 = 1\hspace{0.05cm} {\rm V}$, starting at  $t = T$.
  • $x_3(t)$  is a cosine signal with frequency  $f_0 = 3/T$  and amplitude  $x_0 = 1 \hspace{0.05cm}{\rm V}$.





Hints:


Question

1

For which of the three signals is it more appropriate to calculate the output signal directly in the time domain?

$y_1(t) = x_1(t) \ast h(t)$.
$y_2(t) = x_2(t) \ast h(t)$.
$y_3(t) = x_3(t) \ast h(t)$.

2

What is the signal  $y_1(t)$  at the filter output when the DC signal  $x_1(t) = 1 \hspace{0.03cm}{\rm V}$  is applied to the input?  Give the signal value at  $t = 2T$.

$y_1(t=2T)\ = \ $

 ${\rm V}$

3

To which time range between  $t_{\text{min}}$  and  $t_{\text{max}}$  is the output signal  $y_2(t) = x_2(t) \ast h(t)$  limited, i.e. not equal to zero?

$t_{\text{min}}/T\ = \ $

$t_{\text{max}}/T \ = \ $

4

Calculate the values of the signal  $y_2(t)$  at times  $t = 2T$  and  $t = 3T$.

$y_2(t=2T)\ = \ $

 ${\rm V}$
$y_2(t=3T)\ = \ $

 ${\rm V}$

5

What is the output signal  $y_3(t)$, when the cosine signal  $x_3(t)$  is applied to the input?  Give the signal value at  $t =0$.

$y_3(t=0)\ = \ $

 ${\rm V}$


Solution

(1)  The correct answer is 2:

  • Both  $x_1(t)$  and  $x_3(t)$  contain only one frequency, namely  $f = 0$  or  $f = f_0$.  In each case, the diversions via the spectrum is preferable.
  • With the rectangular pulse  $x_2(t)$  the calculation via convolution is more favourable, since the inverse Fourier transform of  $Y_2(f)$  is complicated.


(2)  For the signal  $x_1(t)$  the output signal is also a DC signal, since the following equations apply:

$$Y_1 (f) = X_1 (f) \cdot H(f)\quad {\rm{with}}\quad X_1 (f) = 1\;{\rm{V}} \cdot \delta (f)$$
$$ \Rightarrow Y_1 (f) = 1\;{\rm{V}} \cdot \delta (f) \cdot H( {f = 0} ) = 1\;{\rm{V}} \cdot \delta (f) \; \Rightarrow \; y_1 (t) = 1\;{\rm{V}} \cdot H( {f = 0} ) \hspace{0.15 cm}\underline{= 1\;{\rm{V}}}.$$
  • The calculation via convolution leads to the same result if one takes into account that the integral over the impulse response is equal to  $1$  in the present case.


(3)  The mirrored signal  $x_2(-t)$  has signal components between  $-2T$  and  $-T$.

  • Only a shift by  $T \hspace{-0.1cm}+ \hspace{-0.1cm}\varepsilon$  leads to an overlap with  $h(t)$.  Here  $\varepsilon$  denotes an arbitrarily small but positive time.
  • However, if the shift is greater than  $4T\hspace{-0.1cm} - \hspace{-0.1cm}\varepsilon$, the integration over the product also yields the value zero.  From this follows:
$$t_{\text{min}} \;\underline{= T}, \ \ \ t_{\text{max}} \;\underline{= 4T}.$$


"Rectangle"  $\star$  "Triangle"

(4)  The result of the graphical convolution for the times  $t = 2T$  and  $t = 3T$  can be seen in the adjacent sketch.

  • The value at  $t = 2T$  corresponds to the area highlighted in red:
$$y_2( {t = 2T} ) = \frac{1}{2}\cdot ( {\frac{1}{T} + \frac{1}{ {2T}}} ) \cdot T \cdot x_0 \hspace{0.15 cm}\underline{= 0.75 {\rm V}} .$$
  • The green highlighted area indicates the value at  $t = 3T$:
$$y_2( {t = 3T} ) = \frac{1}{2}\cdot ( {\frac{1}{2T} + 0} ) \cdot T \cdot x_0 \hspace{0.15 cm}\underline{= 0.25 {\rm V}} .$$

To calculate the entire signal curve between  $t = T$  and  $t = 4T$  three areas must be considered separately. To simplify the representation,  $x_0 = 1$  is set in the following   ⇒   amplitude normalisation.


(4a)  For  $T \leq t \leq 2T$  the lower  $($German:  "untere"   ⇒   "u"$)$  limit is  $τ_u = 0$, and the upper  $($German:  "obere"   ⇒   "o"$)$  limit is  $τ_0 = t - T$:

Convolution for  $T \leq t \leq 2T$
$$y_2 (t) = \int_{\tau _u }^{\tau _0 } {h(\tau )\,{\rm{d}}\tau = \int_0^{t - T} {\frac{1}{T}} }\cdot \left( {1 - \frac{\tau }{ {2T}}} \right)\,{\rm{d}}\tau .$$
  • With the indefinite integral   $I(\tau ) = {\tau }/{T} - 0.25 \cdot \left( {{\tau }/{T}} \right)^2$   we obtain
$$y_2 (t) = I(t - T) - I(0) = \frac{ {t - T}}{T} - 0.25 \cdot \left( {\frac{ {t - T}}{T}} \right)^2 $$
$$\Rightarrow \hspace{0.3cm}y_2 (t) = 1.5 \cdot {t}/{T} - 0.25\cdot \left( {{t}/{T}} \right)^2 - 1.25.$$
  • For verification we consider the two limits.  We get the values  $y_2(T) = 0$  and  $y_2(2T) = 0.75$.


Convolution for  $2T \leq t \leq 3T$

(4b)  In the interval  $2T \leq t \leq 3T$,  the lower limit  $τ_0 = t - T$  still holds, while now  $τ_u = t - 2T$:

$$y_2 (t) = I(t - T) - I(t - 2T) = 1.75 - 0.5 \cdot {t}/{T}.$$

This corresponds to a linear decrease with the two limit values:

$$y_2(2T) = 0.75,$$
$$y_2(3T) = 0.25.$$


Convolution for  $3T \leq t \leq 4T$

(4c)  For the interval  $3T \leq t \leq 4T$  and  $τ_0 = 2T$  und   $τ_u = t - 2T$:

$$y_2 (t) = I(2T) - I(t - 2T) = - 2 \cdot {t}/{T} + 0.25\left( {c{t}/{T}} \right)^2 + 4.$$

Here, too, the correct limit values result:

$$y_2 (3T) = 0.25,$$
$$y_2 (4T) = 0.$$


(5)  In principle, this sub-task could also be solved directly with the convolution.

  • However, since  $x_3(t)$  is an even function, the mirror can now be dispensed and we obtain:
$$y_3 (t) = \int_{ - \infty }^{ + \infty } {h(\tau ) \cdot x_3 (t + \tau )\hspace{0.1cm}{\rm{d}}\tau = x_0 }\cdot \int_0^{2T} {h(\tau ) \cdot \cos (2{\rm{\pi }}f_0 (t + \tau )\hspace{0.1cm}{\rm{d}}\tau .}$$
  • The simpler way here is via the spectra.  $X(f)$  consists of two diraclines at  $\pm 3f_0$.  Thus, the frequency response must also only be calculated for this frequency:
$$H( {f = 3f_0 } ) = \frac{1}{ {72{\rm{\pi }}^{\rm{2}} }}\big[ {1 - {\rm{j}}\cdot 12{\rm{\pi }} - {\rm{cos}}( {{\rm{12\pi }}} ) + {\rm{j}}\cdot \sin ( {{\rm{12\pi }}})} \big] = \frac{1}{ {72{\rm{\pi }}^{\rm{2}} }}\big[ 1 - {\rm j}\cdot 12{\rm \pi } - 1 + {\rm j}\cdot 0 \big]= { - {\rm{j}}} \cdot \frac{1}{ {6{\rm{\pi }}}}.$$
  • Thus the spectrum of the output signal is:
$$Y(f) = - {\rm{j}} \cdot \frac{ {x_0 }}{{{\rm{12\pi }}}}\cdot \delta \left( {f - 3f_0 } \right) + {\rm{j}} \cdot \frac{ {x_0 }}{{{\rm{12\pi }}}}\cdot \delta \left( {f + 3f_0 } \right).$$
  • The signal  $y_3(t)$  is thus sinusoidal with amplitude  $x_0/(6\pi )$.
  • At  $t = 0$  the signal value  $y_3(t = 0)\; \underline{= 0}$ results.