Difference between revisions of "Aufgaben:Exercise 5.1: Sampling Theorem"

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[[File:P_ID1126__Sig_A_5_1.png|right|frame|Zur Abtastung eines analogen Signals  $x(t)$]]
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[[File:P_ID1126__Sig_A_5_1.png|right|frame|Sampling of an analog signal  $x(t)$]]
  
Given is an analogue signal  $x(t)$  according to the sketch:  
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Given is an analog signal  $x(t)$  according to the sketch:  
*It is known that this signal does not contain any frequencies higher than  $B_{\rm NF} = 4 \ \text{kHz}$ .  
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*It is known that this signal does not contain any frequencies higher than  $B_{\rm NF} = 4 \ \text{kHz}$.  
 
*By sampling with the sampling rate  $f_{\rm A}$ , the signal  $x_{\rm A}(t)$ sketched in red in the diagram is obtained.
 
*By sampling with the sampling rate  $f_{\rm A}$ , the signal  $x_{\rm A}(t)$ sketched in red in the diagram is obtained.
 
*For signal reconstruction a low-pass filter is used, for whose frequency response applies:
 
*For signal reconstruction a low-pass filter is used, for whose frequency response applies:
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''Hints:''  
 
''Hints:''  
*This task belongs to the chapter  [[Signal_Representation/Time_Discrete_Signal_Representation|Time Discrete Signal Representation]].
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*This task belongs to the chapter  [[Signal_Representation/Time_Discrete_Signal_Representation|Discrete-Time Signal Representation]].
 
   
 
   
*There is an interactive applet for the topic dealt with here:  [[Applets:Abtastung_periodischer_Signale_und_Signalrekonstruktion_(Applet)|Abtastung periodischer Signale & Signalrekonstruktion]]
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*There is an interactive applet for the topic dealt with here:  [[Applets:Sampling_of_Analog_Signals_and_Signal_Reconstruction|Sampling of Analog Signals and Signal Reconstruction]]
  
  
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$f_{1,\ \text{min}}\ = \ ${ 4 3% }  $\text{kHz}$
 
$f_{1,\ \text{min}}\ = \ ${ 4 3% }  $\text{kHz}$
  
{What is the maximum size of the upper corner frequency  $f_2$  for the signal to be perfectly reconstructed?
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{What is the maximum size of the upper corner frequency  $f_2$  that the signal is perfectly reconstructed?
 
|type="{}"}
 
|type="{}"}
 
$f_{2,\ \text{max}}\ = \ ${ 6 3% }  $\text{kHz}$
 
$f_{2,\ \text{max}}\ = \ ${ 6 3% }  $\text{kHz}$
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===Solution===
 
===Solution===
 
{{ML-Kopf}}
 
{{ML-Kopf}}
'''(1)'''   The distance between two adjacent samples is  $T_{\rm A} = 0.1 \ \text{ms}$. Thus, for the sampling rate  $f_{\rm A} = 1/ T_{\rm A} \;\underline {= 10 \ \text{kHz}}$is obtained.
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'''(1)'''   The distance between two adjacent samples is  $T_{\rm A} = 0.1 \ \text{ms}$.  Thus, for the sampling rate  $f_{\rm A} = 1/ T_{\rm A} \;\underline {= 10 \ \text{kHz}}$is obtained.
  
  
[[File:P_ID1127__Sig_A_5_1_b.png|450px|right|frame|Spectrum  $X_{\rm A}(f)$  of the sampled signal (schematic representation)]]
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[[File:P_ID1127__Sig_A_5_1_b.png|450px|right|frame|Spectrum&nbsp; $X_{\rm A}(f)$&nbsp; of the sampled signal <br>(schematic representation)]]
 
'''(2)'''&nbsp;  Proposed <u>solutions 2 and 4</u> are correct:
 
'''(2)'''&nbsp;  Proposed <u>solutions 2 and 4</u> are correct:
 
*The spectrum&nbsp; $X_{\rm A}(f)$&nbsp; of the sampled signal is obtained from&nbsp; $X(f)$&nbsp; by periodic continuation at a distance of&nbsp; $f_{\rm A} =  10 \ \text{kHz}$.  
 
*The spectrum&nbsp; $X_{\rm A}(f)$&nbsp; of the sampled signal is obtained from&nbsp; $X(f)$&nbsp; by periodic continuation at a distance of&nbsp; $f_{\rm A} =  10 \ \text{kHz}$.  
*From the sketch you can see that&nbsp; $X_{\rm A}(f)$&nbsp; can have parts at&nbsp; $f =  2.5 \ \text{kHz}$&nbsp; and&nbsp;  $f =  6.5 \ \text{kHz}$&nbsp;.
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*From the sketch you can see that&nbsp; $X_{\rm A}(f)$&nbsp; can have signal parts at&nbsp; $f =  2.5 \ \text{kHz}$&nbsp; and&nbsp;  $f =  6.5 \ \text{kHz}$;.
*In contrast, there are no components at&nbsp;  $f =  5.5 \ \text{kHz}$&nbsp;.
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*In contrast, there are no components at&nbsp;  $f =  5.5 \ \text{kHz}$.
*Also at&nbsp;  $f =  34.5 \ \text{kHz}$&nbsp; will be valid in any case.&nbsp; $X_{\rm A}(f) = 0$&nbsp;.
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*Also at&nbsp;  $f =  34.5 \ \text{kHz}$&nbsp; will be valid&nbsp; $X_{\rm A}(f) = 0$.
 
<br clear=all>
 
<br clear=all>
'''(3)'''&nbsp; It must be ensured that all frequencies of the analogue signal are weighted with&nbsp; $H(f) = 1$&nbsp;.
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'''(3)'''&nbsp; It must be ensured that all frequencies of the analog signal are weighted with&nbsp; $H(f) = 1$.
 
*From this follows according to the sketch:  
 
*From this follows according to the sketch:  
  
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'''(4)'''&nbsp; Likewise, it must be guaranteed that all spectral components of&nbsp; $X_{\rm A}(f)$, that are not contained in&nbsp; $X(f)$&nbsp; are removed by the low-pass filter.  
 
'''(4)'''&nbsp; Likewise, it must be guaranteed that all spectral components of&nbsp; $X_{\rm A}(f)$, that are not contained in&nbsp; $X(f)$&nbsp; are removed by the low-pass filter.  
*According to the sketch, the following must therefore apply:
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*According to the sketch, the following must apply:
  
 
:$$f_{2, \ \text{max}} = f_{\rm A} – B_{\rm NF} \;\underline{= 6 \ \text{kHz}}.$$
 
:$$f_{2, \ \text{max}} = f_{\rm A} – B_{\rm NF} \;\underline{= 6 \ \text{kHz}}.$$
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__NOEDITSECTION__
 
__NOEDITSECTION__
[[Category:Exercises for Signal Representation|^5.1 Time Discrete Signal Representation^]]
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[[Category:Signal Representation: Exercises|^5.1 Discrete-Time Signal Representation^]]

Latest revision as of 10:03, 11 October 2021

Sampling of an analog signal  $x(t)$

Given is an analog signal  $x(t)$  according to the sketch:

  • It is known that this signal does not contain any frequencies higher than  $B_{\rm NF} = 4 \ \text{kHz}$.
  • By sampling with the sampling rate  $f_{\rm A}$ , the signal  $x_{\rm A}(t)$ sketched in red in the diagram is obtained.
  • For signal reconstruction a low-pass filter is used, for whose frequency response applies:
$$H(f) = \left\{ \begin{array}{c} 1 \\ 0 \\ \end{array} \right.\quad \begin{array}{*{5}c} {\rm{{\rm{f\ddot{u}r}}}} \\ {\rm{{\rm{f\ddot{u}r}}}} \\ \end{array}\begin{array}{*{5}c} |f| < f_1 \hspace{0.05cm}, \\ |f| > f_2 \hspace{0.05cm} \\ \end{array}$$

The range between the frequencies  $f_1$  and  $f_2 > f_1$  is not relevant for the solution of this task.

The corner frequencies  $f_1$  and  $f_2$  are to be determined in such a way that the output signal  $y(t)$  of the low-pass filter exactly matches the signal  $x(t)$ .





Hints:


Questions

1

Determine the underlying sampling rate from the graph.

$f_{\rm A}\ = \ $

 $\text{kHz}$

2

At which frequencies does the spectral function  $X_{\rm A}(f)$  have no components with certainty?

$f = 2.5 \ \text{kHz},$
$f= 5.5 \ \text{kHz},$
$f= 6.5 \ \text{kHz},$
$f= 34.5 \ \text{kHz}.$

3

What is the minimum size of the lower cut-off frequency  $f_1$  that the signal is perfectly reconstructed?

$f_{1,\ \text{min}}\ = \ $

 $\text{kHz}$

4

What is the maximum size of the upper corner frequency  $f_2$  that the signal is perfectly reconstructed?

$f_{2,\ \text{max}}\ = \ $

 $\text{kHz}$


Solution

(1)  The distance between two adjacent samples is  $T_{\rm A} = 0.1 \ \text{ms}$.  Thus, for the sampling rate  $f_{\rm A} = 1/ T_{\rm A} \;\underline {= 10 \ \text{kHz}}$is obtained.


Spectrum  $X_{\rm A}(f)$  of the sampled signal
(schematic representation)

(2)  Proposed solutions 2 and 4 are correct:

  • The spectrum  $X_{\rm A}(f)$  of the sampled signal is obtained from  $X(f)$  by periodic continuation at a distance of  $f_{\rm A} = 10 \ \text{kHz}$.
  • From the sketch you can see that  $X_{\rm A}(f)$  can have signal parts at  $f = 2.5 \ \text{kHz}$  and  $f = 6.5 \ \text{kHz}$;.
  • In contrast, there are no components at  $f = 5.5 \ \text{kHz}$.
  • Also at  $f = 34.5 \ \text{kHz}$  will be valid  $X_{\rm A}(f) = 0$.


(3)  It must be ensured that all frequencies of the analog signal are weighted with  $H(f) = 1$.

  • From this follows according to the sketch:
$$f_{1, \ \text{min}} = B_{\rm NF} \;\underline{= 4 \ \text{kHz}}.$$


(4)  Likewise, it must be guaranteed that all spectral components of  $X_{\rm A}(f)$, that are not contained in  $X(f)$  are removed by the low-pass filter.

  • According to the sketch, the following must apply:
$$f_{2, \ \text{max}} = f_{\rm A} – B_{\rm NF} \;\underline{= 6 \ \text{kHz}}.$$