Difference between revisions of "Aufgaben:Exercise 5.3: 1st order Digital Filter"

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===Solution===
 
===Solution===
 
{{ML-Kopf}}
 
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'''(1)'''&nbsp; <u>Solutions 2 and 3</u> are correct:
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'''(1)'''&nbsp; <u>Solutions 2 and 3</u>&nbsp; are correct:
 
*The filter is non-recursive if the feedback is omitted: &nbsp; $b_1 = 0$.
 
*The filter is non-recursive if the feedback is omitted: &nbsp; $b_1 = 0$.
*If additionally&nbsp; $a_0 = 1$&nbsp; and&nbsp; $a_1 = 0$, the sequences&nbsp; $\left\langle {x_\nu  } \right\rangle$&nbsp; and&nbsp; $\left\langle {y_\nu  } \right\rangle$&nbsp; and thus of course the signals&nbsp; $x(t)$&nbsp; and&nbsp; $y(t)$&nbsp; are equal.
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*If additionally&nbsp; $a_0 = 1$&nbsp; and&nbsp; $a_1 = 0$,&nbsp; the sequences&nbsp; $\left\langle {x_\nu  } \right\rangle$&nbsp; and&nbsp; $\left\langle {y_\nu  } \right\rangle$&nbsp; and thus of course the signals&nbsp; $x(t)$&nbsp; and&nbsp; $y(t)$&nbsp; are equal.
 
*With&nbsp; $a_0 = 0$&nbsp; and&nbsp; $a_1 = 1$,&nbsp; &nbsp;  $y(t) = x(t-T_{\rm A})$&nbsp; is delayed by&nbsp; $T_{\rm A}$&nbsp; with&nbsp; $a_1 = 0.5$&nbsp; additionally attenuated.
 
*With&nbsp; $a_0 = 0$&nbsp; and&nbsp; $a_1 = 1$,&nbsp; &nbsp;  $y(t) = x(t-T_{\rm A})$&nbsp; is delayed by&nbsp; $T_{\rm A}$&nbsp; with&nbsp; $a_1 = 0.5$&nbsp; additionally attenuated.
*However, delay and damping do not result in distortion.  
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*However,&nbsp; delay and damping do not result in distortion.  
  
  
  
'''(2)'''&nbsp; At time&nbsp; $\nu = 0$,&nbsp; &nbsp; $y_{\nu} = x_{\nu} = 1$.&nbsp; For all further time points&nbsp; $\nu$,&nbsp; &nbsp; $x_{\nu} = 0$&nbsp; and thus:
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'''(2)'''&nbsp; At time&nbsp; $\nu = 0$:&nbsp; &nbsp; $y_{\nu} = x_{\nu} = 1$.&nbsp;  
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*For all further time points:&nbsp; $\nu$,&nbsp; &nbsp; $x_{\nu} = 0$&nbsp; and thus:
 
:$$y_\nu  = b_1  \cdot y_{\nu  - 1}  = {b_1 }^\nu  .$$
 
:$$y_\nu  = b_1  \cdot y_{\nu  - 1}  = {b_1 }^\nu  .$$
In particular,&nbsp; $y_3 = b_1^3 = 0.6^3\hspace{0.15cm}\underline{= 0.216}$.
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*In particular,&nbsp; $y_3 = b_1^3 = 0.6^3\hspace{0.15cm}\underline{= 0.216}$.
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'''(4)'''&nbsp; Due to the linearity of the present filter, the same result is obtained if
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'''(4)'''&nbsp; Due to the linearity of the present filter,&nbsp; the same result is obtained
*the filter is not changed compared to subtask&nbsp; '''(2)'''&nbsp; &nbsp; $(a_1 = 0)$  
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*if the filter is not changed compared to subtask&nbsp; '''(2)'''&nbsp; &nbsp; $(a_1 = 0)$  
 
*and the input sequence &nbsp; $\left\langle {x_\nu  } \right\rangle  = \left\langle {1,\; - 0.5,\;0,\;0,\;\text{...} } \right\rangle$&nbsp; is considered.
 
*and the input sequence &nbsp; $\left\langle {x_\nu  } \right\rangle  = \left\langle {1,\; - 0.5,\;0,\;0,\;\text{...} } \right\rangle$&nbsp; is considered.
  
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*With &nbsp;$b_1 = 0.6$&nbsp; and &nbsp;$a_1 = -0.5$,&nbsp; this gives &nbsp;$y_\nu  = 0.1\cdot {0.6} ^{\nu  - 1}$,&nbsp; and thus the sequence &nbsp;  $\left\langle {y_\nu  } \right\rangle  = \left\langle {1,\;0.1,\;0.06,\;0.036,\;\text{...} } \right\rangle .$
 
*With &nbsp;$b_1 = 0.6$&nbsp; and &nbsp;$a_1 = -0.5$,&nbsp; this gives &nbsp;$y_\nu  = 0.1\cdot {0.6} ^{\nu  - 1}$,&nbsp; and thus the sequence &nbsp;  $\left\langle {y_\nu  } \right\rangle  = \left\langle {1,\;0.1,\;0.06,\;0.036,\;\text{...} } \right\rangle .$
  
*The value we are looking for is&nbsp; $y_4\hspace{0.15cm}\underline{= 0.036}$.
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*The value we are looking for is&nbsp; $y_3\hspace{0.15cm}\underline{= 0.036}$.
 
{{ML-Fuß}}
 
{{ML-Fuß}}
  

Latest revision as of 19:00, 10 February 2022

First order digital filter

We consider the filter arrangement shown on the right with coefficients  $a_0$,  $a_1$  and  $b_1$,  each of which can take values between  $0$  and  $1$. 

  • Let the input signal  $x(t)$  be a single Dirac delta impulse with unit weight  "1"   ⇒   $x(t) = \delta(t)$,  which corresponds to the following discrete-time representation:
$$\left\langle {\hspace{0.05cm}x_\nu } \hspace{0.05cm}\right\rangle = \left\langle \hspace{0.05cm}1,\;0,\;0,\;0,\;\text{...} \hspace{0.05cm}\right\rangle .$$
  • Due to this special input sequence,  the sequence  $\left\langle {\hspace{0.05cm}y_\nu \hspace{0.05cm}} \right\rangle$  at the filter output simultaneously describes the discrete-time impulse response  $\left\langle {\hspace{0.05cm}h_\nu \hspace{0.05cm}} \right\rangle$  of the filter.  The spacing of the samples here is  $T_{\rm A} = 1 \hspace{0.05cm} \rm µ s$.



Note:


Questions

1

Which of the following statements are true?

The special case  $b_1 = 1$  leads to a non-recursive filter.
With  $a_0 = 1$,  $a_1 = 0$  and  $b_1 = 0$:    $y(t) = x(t)$  is true.
With  $a_0 = 0$,  $a_1 = 0.5$  and  $b_1 = 0$:   $y(t)$  is undistorted with respect to  $x(t)$. 

2

Let now  $a_0 = 1$,  $a_1 = 0$  and  $b_1 = 0.6$.  Calculate the output sequence  $\left\langle {y_\nu } \right\rangle$.  What output value  $y_3$  occurs at time  $t = 3 \cdot T_{\rm A}$? 

$y_3 \ = \ $

3

Let  $a_0 = 1$,  $a_1 = 0$  and  $b_1 = 0.6$.  On which range  $0$, ... , $M \cdot T_{\rm A}$  is the impulse response limited to if values smaller than  $0.001$  are neglected?

$M \ = \ $

4

Let  $a_0 = 1$  and  $b_1 = 0.6$.  Given the result from  (2),  calculate the output value  $y_3$  for  $a_1 = -0.5$.

$y_3 \ = \ $


Solution

(1)  Solutions 2 and 3  are correct:

  • The filter is non-recursive if the feedback is omitted:   $b_1 = 0$.
  • If additionally  $a_0 = 1$  and  $a_1 = 0$,  the sequences  $\left\langle {x_\nu } \right\rangle$  and  $\left\langle {y_\nu } \right\rangle$  and thus of course the signals  $x(t)$  and  $y(t)$  are equal.
  • With  $a_0 = 0$  and  $a_1 = 1$,    $y(t) = x(t-T_{\rm A})$  is delayed by  $T_{\rm A}$  with  $a_1 = 0.5$  additionally attenuated.
  • However,  delay and damping do not result in distortion.


(2)  At time  $\nu = 0$:    $y_{\nu} = x_{\nu} = 1$. 

  • For all further time points:  $\nu$,    $x_{\nu} = 0$  and thus:
$$y_\nu = b_1 \cdot y_{\nu - 1} = {b_1 }^\nu .$$
  • In particular,  $y_3 = b_1^3 = 0.6^3\hspace{0.15cm}\underline{= 0.216}$.


(3)  According to the problem definition must be valid:  

$$y_{M + 1} = {b_1} ^{M + 1} < 0.001.$$
  • This leads to the result:
$$M + 1 \ge \frac{{\lg \ \left( {0.001} \right)}}{{\lg \ \left( {0.6} \right)}} = \frac{ - 3}{ - 0.222} \approx 13.51\quad \Rightarrow \quad \hspace{0.15cm} \underline{M = 13}.$$
  • Checking the values of  $y_{13} \approx 0.0013$  and  $y_{14} \approx 0.0008$  confirms this result.


(4)  Due to the linearity of the present filter,  the same result is obtained

  • if the filter is not changed compared to subtask  (2)    $(a_1 = 0)$
  • and the input sequence   $\left\langle {x_\nu } \right\rangle = \left\langle {1,\; - 0.5,\;0,\;0,\;\text{...} } \right\rangle$  is considered.


One then obtains in general for  $\nu \gt 0$:

$$y_\nu = {b_1} ^\nu + a_1 \cdot {b_1} ^{\nu - 1} = \left( {b_1 + a_1 } \right) \cdot {b_1} ^{\nu - 1} .$$
  • With  $b_1 = 0.6$  and  $a_1 = -0.5$,  this gives  $y_\nu = 0.1\cdot {0.6} ^{\nu - 1}$,  and thus the sequence   $\left\langle {y_\nu } \right\rangle = \left\langle {1,\;0.1,\;0.06,\;0.036,\;\text{...} } \right\rangle .$
  • The value we are looking for is  $y_3\hspace{0.15cm}\underline{= 0.036}$.