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

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{{quiz-Header|Buchseite=Stochastische Signaltheorie/Digitale Filter
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{{quiz-Header|Buchseite=Theory_of_Stochastic_Signals/Digital_Filters
 
}}
 
}}
  
[[File:P_ID607__Sto_A_5_3.png|right|frame|Digitales Filter erster Ordnung]]
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[[File:P_ID607__Sto_A_5_3.png|right|frame|First order digital filter]]
Wir betrachten die nebenstehende Filteranordnung mit den Koeffizienten $a_0$, $a_1$ und $b_1$, die jeweils Werte zwischen $0$ und $1$ annehmen können.
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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  $1$. 
  
*Das Eingangssignal $x(t)$ sei  ein einziger Diracimpuls mit dem Einheitsgewicht „1”   ⇒    $x(t) = \delta(t)$, was der folgenden zeitdiskreten Darstellung entspricht:
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*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:
 
:$$\left\langle {\hspace{0.05cm}x_\nu  } \hspace{0.05cm}\right\rangle  = \left\langle \hspace{0.05cm}1,\;0,\;0,\;0,\;\text{...} \hspace{0.05cm}\right\rangle .$$
 
:$$\left\langle {\hspace{0.05cm}x_\nu  } \hspace{0.05cm}\right\rangle  = \left\langle \hspace{0.05cm}1,\;0,\;0,\;0,\;\text{...} \hspace{0.05cm}\right\rangle .$$
  
*Aufgrund dieser speziellen Eingangsfolge beschreibt die Folge $\left\langle {\hspace{0.05cm}y_\nu  \hspace{0.05cm}} \right\rangle$ am Filterausgang gleichzeitig die zeitdiskrete Impulsantwort des Filters. Der Abstand der Abtastwerte beträgt hierbei $T_{\rm A} = 1 \hspace{0.05cm} \rm µ s$.
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*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  $T_{\rm A} = 1 \hspace{0.05cm} \rm µ s$.
  
  
  
''Hinweis:''
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*Die Aufgabe gehört zum  Kapitel [[Stochastische_Signaltheorie/Digitale_Filter|Digitale Filter]].
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Note:  
 +
*The exercise belongs to the chapter  [[Theory_of_Stochastic_Signals/Digital_Filters|Digital Filters]].
 +
*The HTML5/JavaScript applet  [[Applets:Digital_Filters|"Digital Filters"]]  illustrates the subject matter of this chapter.
 
   
 
   
  
  
===Fragebogen===
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===Questions===
  
 
<quiz display=simple>
 
<quiz display=simple>
{Welche der folgenden Aussagen sind zutreffend?
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{Which of the following statements are true?
 
|type="[]"}
 
|type="[]"}
- Der Sonderfall &nbsp;$b_1 = 1$&nbsp; führt zu einem nichtrekursiven Filter.
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- The special case &nbsp;$b_1 = 1$&nbsp; leads to a non-recursive filter.
+ Mit &nbsp;$a_0 = 1$, $a_1 = 0$ &nbsp;und&nbsp; $b_1 = 0$ &nbsp;gilt&nbsp; $y(t) = x(t)$.
+
+ With &nbsp;$a_0 = 1$,&nbsp; $a_1 = 0$ &nbsp;and&nbsp; $b_1 = 0$:&nbsp; &nbsp; $y(t) = x(t)$&nbsp;  is true.
+ Mit &nbsp;$a_0 = 0$, $a_1 = 0.5$ &nbsp;und&nbsp; $b_1 = 0$ ist &nbsp;$y(t)$&nbsp; gegenüber &nbsp;$x(t)$&nbsp; unverzerrt.
+
+ With &nbsp;$a_0 = 0$,&nbsp; $a_1 = 0.5$ &nbsp;and&nbsp; $b_1 = 0$:&nbsp; &nbsp;$y(t)$&nbsp; is undistorted with respect to &nbsp;$x(t)$.&nbsp;  
  
  
{Es gelte nun $a_0 = 1$, $a_1 = 0$ und $b_1 = 0.6$. Berechnen Sie die Ausgangsfolge $\left\langle {y_\nu  } \right\rangle$. <br>Welcher Ausgangswert $y_3$ tritt zum Zeitpunkt $t = 3 \cdot T_{\rm A}$ auf?
+
{Let now&nbsp; $a_0 = 1$,&nbsp; $a_1 = 0$&nbsp; and&nbsp; $b_1 = 0.6$.&nbsp; Calculate the output sequence&nbsp; $\left\langle {y_\nu  } \right\rangle$.&nbsp; What output value&nbsp; $y_3$&nbsp; occurs at time&nbsp; $t = 3 \cdot T_{\rm A}$?&nbsp;
 
|type="{}"}
 
|type="{}"}
 
$y_3 \ = \ $  { 0.216 3% }
 
$y_3 \ = \ $  { 0.216 3% }
  
  
{Es gelte weiter $a_0 = 1$, $a_1 = 0$ und $b_1 = 0.6$. Auf welchen Bereich $0$, ... , $M \cdot T_{\rm A}$ ist die Impulsantwort beschränkt, <br>wenn man Werte kleiner als $0.001$ vernachlässigt?  
+
{Let&nbsp; $a_0 = 1$,&nbsp; $a_1 = 0$&nbsp; and&nbsp; $b_1 = 0.6$.&nbsp; On which range&nbsp; $0$, ... , $M \cdot T_{\rm A}$&nbsp; is the impulse response limited to if values smaller than&nbsp; $0.001$&nbsp; are neglected?
 
|type="{}"}
 
|type="{}"}
 
$M \ =  \ ${ 13 3% }
 
$M \ =  \ ${ 13 3% }
  
  
{Weiter gelte $a_0 = 1$ und $b_1 = 0.6$. Berechnen Sie unter Berücksichtigung des Ergebnisses aus (2) den Ausgangswert $y_3$ für $a_1 = -0.5$.
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{Let&nbsp; $a_0 = 1$&nbsp; and&nbsp; $b_1 = 0.6$.&nbsp; Given the result from&nbsp; '''(2)''',&nbsp; calculate the output value&nbsp; $y_3$&nbsp; for&nbsp; $a_1 = -0.5$.
 
|type="{}"}
 
|type="{}"}
 
$y_3 \ =  \ $ { 0.036 3% }
 
$y_3 \ =  \ $ { 0.036 3% }
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</quiz>
 
</quiz>
  
===Musterlösung===
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===Solution===
 
{{ML-Kopf}}
 
{{ML-Kopf}}
'''(1)'''&nbsp; Richtig sind die <u>Lösungsvorschläge 2 und 3</u>:
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'''(1)'''&nbsp; <u>Solutions 2 and 3</u>&nbsp; are correct:
*Das Filter ist nichtrekursiv, wenn die Rückführung entfällt: &nbsp; $b_1 = 0$.
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*The filter is non-recursive if the feedback is omitted: &nbsp; $b_1 = 0$.
*Sind zusätzlich $a_0 = 1$ und $a_1 = 0$, so sind die Folgen $\left\langle {x_\nu  } \right\rangle$ und $\left\langle {y_\nu  } \right\rangle$und damit natürlich auch die Signale $x(t)$ und $y(t)$ gleich.  
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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.
*Mit $a_0 = 0$ und $a_1 = 1$ ist $y(t) = x(t-T_{\rm A})$ um $T_{\rm A}$ verzögert, mit $a_1 = 0.5$ zusätzlich gedämpft.  
+
*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.
*Verzögerung und Dämpfung haben jedoch keine Verzerrung zur Folge.  
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*However,&nbsp; delay and damping do not result in distortion.  
 +
 
  
  
'''(2)'''&nbsp; Zum Zeitpunkt $\nu = 0$ ist $y_{\nu} = x_{\nu} = 1$. Für alle weiteren Zeitpunkte $\nu$&nbsp; gilt $x_{\nu} = 0$ und somit auch:
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'''(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:
 
:$$y_\nu  = b_1  \cdot y_{\nu  - 1}  = {b_1 }^\nu  .$$
 
:$$y_\nu  = b_1  \cdot y_{\nu  - 1}  = {b_1 }^\nu  .$$
Insbesondere ist $y_3 = b_1^3 = 0.6^3\hspace{0.15cm}\underline{= 0.216}$.
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*In particular,&nbsp; $y_3 = b_1^3 = 0.6^3\hspace{0.15cm}\underline{= 0.216}$.
 +
 
  
  
'''(3)'''&nbsp; Entsprechend der Aufgabenstellung muss gelten: &nbsp;  $y_{M + 1}  = {b_1} ^{M + 1}  < 0.001.$ Dies führt zum Ergebnis:
+
'''(3)'''&nbsp; According to the problem definition must be valid: &nbsp;   
 +
:$$y_{M + 1}  = {b_1} ^{M + 1}  < 0.001.$$
 +
*This leads to the result:
 
:$$M + 1 \ge \frac{{\lg \ \left( {0.001} \right)}}{{\lg \ \left( {0.6} \right)}} = \frac{ - 3}{ - 0.222} \approx 13.51\quad  \Rightarrow \quad  \hspace{0.15cm} \underline{M = 13}.$$
 
:$$M + 1 \ge \frac{{\lg \ \left( {0.001} \right)}}{{\lg \ \left( {0.6} \right)}} = \frac{ - 3}{ - 0.222} \approx 13.51\quad  \Rightarrow \quad  \hspace{0.15cm} \underline{M = 13}.$$
  
Die Überprüfung der Werte $y_{13} \approx 0.0013$ und $y_{14} \approx 0.0008$ bestätigt dieses Ergebnis.
+
*Checking the values of&nbsp; $y_{13} \approx 0.0013$&nbsp; and&nbsp; $y_{14} \approx 0.0008$&nbsp; confirms this result.
 +
 
  
  
'''(4)'''&nbsp; Aufgrund der Linearität des vorliegenden Filters erhält man das gleiche Ergebnis, wenn man
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'''(4)'''&nbsp; Due to the linearity of the present filter,&nbsp; the same result is obtained
*das Filter gegenüber der Teilaufgabe '''(2)''' nicht verändert $(a_1 = 0)$  
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*if the filter is not changed compared to subtask&nbsp; '''(2)'''&nbsp; &nbsp; $(a_1 = 0)$  
*und dafür die Eingangsfolge &nbsp; $\left\langle {x_\nu  } \right\rangle  = \left\langle {1,\; - 0.5,\;0,\;0,\;\text{...} } \right\rangle$ berücksichtigt.  
+
*and the input sequence &nbsp; $\left\langle {x_\nu  } \right\rangle  = \left\langle {1,\; - 0.5,\;0,\;0,\;\text{...} } \right\rangle$&nbsp; is considered.
  
  
Man erhält dann allgemein für $\nu \gt 0$:
+
One then obtains in general for&nbsp; $\nu \gt 0$:
 
:$$y_\nu  = {b_1} ^\nu  + a_1  \cdot {b_1} ^{\nu  - 1}  = \left( {b_1  + a_1 } \right) \cdot {b_1} ^{\nu  - 1} .$$
 
:$$y_\nu  = {b_1} ^\nu  + a_1  \cdot {b_1} ^{\nu  - 1}  = \left( {b_1  + a_1 } \right) \cdot {b_1} ^{\nu  - 1} .$$
  
Mit &nbsp;$b_1 = 0.6$&nbsp; und &nbsp;$a_1 = -0.5$&nbsp; ergibt sich daraus &nbsp;$y_\nu  = 0.1\cdot {0.6} ^{\nu  - 1} ,$&nbsp;
+
*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;  $\left\langle {y_\nu  } \right\rangle  = \left\langle {1,\;0.1,\;0.06,\;0.036,\;\text{...} } \right\rangle .$
und somit die Folge &nbsp;  $\left\langle {y_\nu  } \right\rangle  = \left\langle {1,\;0.1,\;0.06,\;0.036,\;\text{...} } \right\rangle .$
 
  
Der gesuchte Wert ist $y_4\hspace{0.15cm}\underline{= 0.036}$.
+
*The value we are looking for is&nbsp; $y_3\hspace{0.15cm}\underline{= 0.036}$.
 
{{ML-Fuß}}
 
{{ML-Fuß}}
  
  
  
[[Category:Aufgaben zu Stochastische Signaltheorie|^5.2 Digitale Filter^]]
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[[Category:Theory of Stochastic Signals: Exercises|^5.2 Digital Filters^]]

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  $y_3\hspace{0.15cm}\underline{= 0.036}$.