Difference between revisions of "Aufgaben:Exercise 4.11: C Program "acf1""

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{{quiz-Header|Buchseite=Stochastische Signaltheorie/Autokorrelationsfunktion (AKF)
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{{quiz-Header|Buchseite=Theory_of_Stochastic_Signals/Auto-Correlation_Function
 
}}
 
}}
  
[[File:P_ID391__Sto_A_4_11.png|right|C-Programm 1 zur AKF-Berechnung]]
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[[File:EN_Sto_A_4_11_neu2.png|right|frame|C program  $1$  for the ACF calculation]]
Sie sehen nebenstehend das C-Programm „akf1” zur Berechnung der diskreten AKF-Werte $\varphi_x(k)$ mit dem Index $k = 0$, ... , $l$. Hierzu ist Folgendes zu bemerken:
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See the C–program "acf1" for calculating the discrete ACF values  $\varphi_x(k)$  with index  $k = 0$, ... , $l$.  The following should be noted about this:
  
* Der an das Programm übergebene Long-Wert sei $l = 10$. Die AKF-Werte $\varphi_x(0)$, ... , $\varphi_x(10)$ werden mit dem Float-Feld $\rm AKF[ \ ]$ an das aufrufende Programm zurückgegeben. In den  Zeilen 7 und  8 des rechts anggebenen Programms wird dieses Feld mit Nullen vorbelegt.
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* The long–value passed to the program is  $l = 10$.  The ACF values  $\varphi_x(0)$, ... , $\varphi_x(10)$  are returned to the calling program with the float field  $\rm ACF\big[ \ \big]$.  In lines 7 and 8 of the program given on the right,  this field is pre-populated with zeros.
  
* Die zu analysierenden Zufallsgrößen $x_\nu$ werden mit der Float-Funktion $x( \ )$ erzeugt (siehe Zeile 4). Diese Funktion wird insgesamt $N + l + 1 = 10011$ mal aufgerufen (Zeile 9 und 18).
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* The random variables  $x_\nu$  to be analyzed are generated with the float function  $x( \ )$,  see line 4.  This function is called a total of  $N + l + 1 = 10011$  times  $x_\nu$  (lines 9 and 18).
  
* Im Gegensatz zu dem im [[Stochastische_Signaltheorie/Autokorrelationsfunktion_(AKF)#Numerische_AKF-Ermittlung|Theoriteil]] angegebenen Algorithmus, der im Programm „akf2” von [[Aufgaben:4.11Z_C-Programm_„akf2”|Zusatzaufgabe 4.11]] direkt umgesetzt ist, benötigt man hier ein Hilfsfeld $H[ \ ]$ mit nur $l + 1 = 11$ Speicherelementen.
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* In contrast to the algorithm given in the  [[Theory_of_Stochastic_Signals/Auto-Correlation_Function#Numerical_ACF_determination|Theory section]]  directly implemented in the program  "acf2"  of  [[Aufgaben:Exercise_4.11Z:_C_Program_"acf2"|Task 4.11Z]],  one needs here an auxiliary field  ${\rm H}\big[ \ \big]$  with only  $l + 1 = 11$  memory elements.
  
* Vor Beginn des eigentlichen Berechnungsalgorithmus (Zeile 11 bis 21) stehen in den 11 Speicherzellen die Zufallswerte $x_1$, ... , $x_{11}$.
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* Before starting the actual calculation algorithm (lines 11 to 21),  the eleven memory cells of  ${\rm H}\big[ \ \big]$  contain the random values  $x_1$, ... ,  $x_{11}$.  The outer loop with the index  $z$   (marked in red)  is run  $N$  times.
 +
*In the inner loop   (marked white)  with the index  $k = 0$, ... ,  $l$  all memory cells of the field  ${\rm ACF}\big[\hspace{0.03cm} k \hspace{0.03cm} \big]$  are increased by the contribution  $x_\nu \cdot x_{\nu+k}$.
  
* Die äußere Schleife mit der Laufvariablen $z$ (rot markiert) wird $N$-mal durchlaufen. In der inneren Schleife (weiß markiert) werden mit dem Laufindex $k = 0$, ... , $l$ alle Speicherzellen des Feldes ${\rm AKF}[ k ]$ um den Betrag $x_\nu \cdot x_{\nu+k}$ erhöht.
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* Finally,  in lines 22 and 23,  all ACF values are divided by the number  $N$  of analyzed  data.  
  
* In den Zeilen 22 und 23 werden schließlich alle AKF-Werte durch die Anzahl $N$ dividiert.
 
  
  
''Hinweise:''
 
*Die Aufgabe gehört zum  Kapitel [[Stochastische_Signaltheorie/Autokorrelationsfunktion_(AKF)|Autokorrelationsfunktion]].
 
*Bezug genommen wird insbesondere auf die Seite [[Stochastische_Signaltheorie/Autokorrelationsfunktion_(AKF)#Numerische_AKF-Ermittlung|Numerische AKF-Ermittlung]].
 
*Sollte die Eingabe des Zahlenwertes „0” erforderlich sein, so geben Sie bitte „0.” ein.
 
  
  
  
===Fragebogen===
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Hint:
 +
*This exercise belongs to the chapter  [[Theory_of_Stochastic_Signals/Auto-Correlation_Function|Auto-Correlation Function]].
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*Reference is made in particular to the page  [[Theory_of_Stochastic_Signals/Auto-Correlation_Function#Numerical_ACF_determination|Numerical ACF determination]].
 +
 +
 
 +
 
 +
 
 +
===Questions===
  
 
<quiz display=simple>
 
<quiz display=simple>
{Welche Elemente $i$ und $j$ des Hilfsfeldes $H[ \ ]$ werden beim ersten Durchlauf $(z=0)$ zur Berechnung des AKF-Wertes $\varphi(k=6)$ verwendet? Welche Zufallswerte $x_\nu$ stehen in diesen Speicherzellen?
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{Which elements&nbsp; $i$&nbsp; and&nbsp; $j$&nbsp; of the auxiliary field&nbsp; ${\rm H}\big[ \ \big]$&nbsp; are used&nbsp; <u>on the first loop pass</u> &nbsp; $(z=0)$&nbsp; to calculate the ACF&ndash;value&nbsp; $\varphi(k=6)$&nbsp;? <br>What random values&nbsp; $x_\nu$&nbsp; are in these memory cells?
 
|type="{}"}
 
|type="{}"}
$i \ = $   { 0. }
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$i \ = \ $ { 0. }
$j \ = $ { 6 }
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$j \ = \ $ { 6 }
  
  
{Welche Speicherzelle  $H[ i ]$ wird nach dem ersten Schleifendurchgang $(z=0)$ mit einer neuen Zufallsgr&ouml;&szlig;e $x_\nu$ belegt? Welcher Index $\nu$ wird dabei eingetragen?
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{Which memory cell&nbsp; ${\rm H}\big[\hspace{0.03cm} i \hspace{0.03cm} \big]$&nbsp; will be occupied&nbsp; <u>after the first loop pass</u> &nbsp; $(z=0)$&nbsp; with a new random variable&nbsp; $x_\nu$&nbsp;? <br> Which index &nbsp; $\nu$&nbsp; is entered in the process?  
 
|type="{}"}
 
|type="{}"}
$i \ = $  { 0. }
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$i \ = \ $  { 0. }
$v \ = { 12 }
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$\nu\ =\ $ { 12 }
  
  
{Welche Speicherelemente $H[ i ]$ und $H[ j ]$ werden beim Schleifendurchlauf $z=83$ zur Berechnung des AKF-Wertes $\varphi(k=6)$ verwendet? Welche Zufallswerte stehen in diesen Speicherzellen?
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{Which memory elements&nbsp; ${\rm H}\big[\hspace{0.03cm} i \hspace{0.03cm} \big]$&nbsp; and&nbsp; ${\rm H}\big[\hspace{0.03cm} j \hspace{0.03cm} \big]$&nbsp; are used in the loop pass&nbsp; $z=83$&nbsp; to calculate the ACF value&nbsp; $\varphi(k=6)$&nbsp;? <br>What random values are in these memory cells?
 
|type="{}"}
 
|type="{}"}
$i \ = $  { 6 }
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$i \ = \ $  { 6 }
$j \ = $ { 1 }
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$j \ = \ $ { 1 }
  
  
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</quiz>
 
</quiz>
  
===Musterlösung===
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===Solution===
 
{{ML-Kopf}}
 
{{ML-Kopf}}
:<b>1.</b>&nbsp;&nbsp;Aus <i>z</i> = 0 und <i>k</i> = 6 ergibt sich gem&auml;&szlig; dem Programm: <u><i>i</i> = 0</u> und <u><i>j</i> = 6</u>. Die entsprechenden Speicherinhalte sind <i>H</i>[0] = <i>x</i><sub>1</sub> und <i>H</i>[6] = <i>x</i><sub>7</sub>.
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[[File:P_ID417__Sto_A_4_11_b.png|right|frame|For the exemplary numerical ACF calculation]]
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<br>
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'''(1)'''&nbsp; With&nbsp; $z= 0$&nbsp; and&nbsp; $k=6$&nbsp; results according to the program: &nbsp; $\underline{i= 0}$&nbsp; and&nbsp; $\underline{j= 6}$.
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*The corresponding memory contents are&nbsp; ${\rm H}\big[\hspace{0.03cm} 0 \hspace{0.03cm}\big] = x_1$&nbsp; and&nbsp; ${\rm H}\big[\hspace{0.03cm} 6 \hspace{0.03cm}\big] = x_7$.
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 +
 
 +
 
 +
 
 +
'''(2)'''&nbsp; In the field&nbsp; ${\rm H}\big[\hspace{0.03cm} 0 \hspace{0.03cm}\big]$&nbsp; the random variable&nbsp; $x_{12}$&nbsp; is now entered:
 +
:$$\text{memory cell }\underline{i= 0},\hspace{1cm}\text{sequence index }\underline{\nu= 12}.$$
 +
 
  
:<b>2.</b>&nbsp; &nbsp;In das Feld <i>H</i>[0] wird die Zufallsgr&ouml;&szlig;e <i>x</i><sub>12</sub> eingetragen: <u><i>i</i> = 0, Index <i>&nu;</i> = 12</u>.
 
  
:<b>3.</b>&nbsp;&nbsp;Das nachfolgende Bild zeigt die Belegung des Hilfsfeldes <i>H</i>[0] ... <i>H</i>[10] mit den Zufallswerten <i>x<sub>&nu;</sub></i>. Jeweils gr&uuml;n hinterlegt ist die Speicherzelle <i>H</i>[<i>i</i>]. In diesen Speicherplatz wird jeweils am Ende der Schleife (Zeile 18) die neue Zufallsgr&ouml;&szlig;e eingetragen.
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'''(3)'''&nbsp; The graph shows the allocation of the auxiliary field with the random values&nbsp; $x_\nu$.  
[[File:P_ID417__Sto_A_4_11_b.png|center|]]
 
  
:F&uuml;r <i>z</i> = 83 und <i>k</i> = 6 ergibt sich <u><i>i</i> = 83 mod 11 = 6</u> und <u><i>j</i> = (<i>i</i> + <i>k</i>) mod 11 = 1</u>. In diesen Speicherzellen liegen die Zufallsgr&ouml;&szlig;en <i>x</i><sub>84</sub> und <i>x</i><sub>90</sub>. Am Ende des Schleifendurchlaufs <i>z</i> = 83 wird in <i>H</i>[6] der Wert <i>x</i><sub>84</sub> durch <i>x</i><sub>95</sub> ersetzt.
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*In each case,&nbsp; the memory cell&nbsp; ${\rm H}\big[\hspace{0.03cm} i \hspace{0.03cm}\big]$&nbsp; is highlighted in green.&nbsp; The new random variable is entered into this memory location at the end of each loop&nbsp; (line 18).
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*For&nbsp; $z= 83$&nbsp; and&nbsp; $K=6$&nbsp; this results in
 +
:$$\underline{i= 83 \hspace{-0.2cm}\mod \hspace{-0.15cm} \ 11 = 6},\hspace{1cm} \underline{j= (i+k)\hspace{-0.2cm}\mod \hspace{-0.15cm} \ 11 = 1}.$$
 +
*Loop pass&nbsp; $z= 83$: &nbsp; In memory cell&nbsp; ${\rm H}\big[\hspace{0.03cm} 6 \hspace{0.03cm}\big]$&nbsp; is the random variable&nbsp; $x_{84}$&nbsp; and in the memory cell&nbsp; ${\rm H}\big[\hspace{0.03cm} 1 \hspace{0.03cm}\big]$&nbsp; is the random variable&nbsp; $x_{90}$.  
 +
*At the end of loop pass&nbsp; $z= 83$&nbsp; in&nbsp; ${\rm H}\big[\hspace{0.03cm} 6 \hspace{0.03cm}\big]$:&nbsp; The content&nbsp; $x_{84}$&nbsp; is replaced by&nbsp; $x_{95}$&nbsp;.
 
{{ML-Fuß}}
 
{{ML-Fuß}}
  
  
  
[[Category:Aufgaben zu Stochastische Signaltheorie|^4.4 Autokorrelationsfunktion (AKF)^]]
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[[Category:Theory of Stochastic Signals: Exercises|^4.4 Auto-Correlation Function^]]

Latest revision as of 16:28, 28 April 2022

C program  $1$  for the ACF calculation

See the C–program "acf1" for calculating the discrete ACF values  $\varphi_x(k)$  with index  $k = 0$, ... , $l$.  The following should be noted about this:

  • The long–value passed to the program is  $l = 10$.  The ACF values  $\varphi_x(0)$, ... , $\varphi_x(10)$  are returned to the calling program with the float field  $\rm ACF\big[ \ \big]$.  In lines 7 and 8 of the program given on the right,  this field is pre-populated with zeros.
  • The random variables  $x_\nu$  to be analyzed are generated with the float function  $x( \ )$,  see line 4.  This function is called a total of  $N + l + 1 = 10011$  times  $x_\nu$  (lines 9 and 18).
  • In contrast to the algorithm given in the  Theory section  directly implemented in the program  "acf2"  of  Task 4.11Z,  one needs here an auxiliary field  ${\rm H}\big[ \ \big]$  with only  $l + 1 = 11$  memory elements.
  • Before starting the actual calculation algorithm (lines 11 to 21),  the eleven memory cells of  ${\rm H}\big[ \ \big]$  contain the random values  $x_1$, ... ,  $x_{11}$.  The outer loop with the index  $z$   (marked in red)  is run  $N$  times.
  • In the inner loop   (marked white)  with the index  $k = 0$, ... ,  $l$  all memory cells of the field  ${\rm ACF}\big[\hspace{0.03cm} k \hspace{0.03cm} \big]$  are increased by the contribution  $x_\nu \cdot x_{\nu+k}$.
  • Finally,  in lines 22 and 23,  all ACF values are divided by the number  $N$  of analyzed data.




Hint:



Questions

1

Which elements  $i$  and  $j$  of the auxiliary field  ${\rm H}\big[ \ \big]$  are used  on the first loop pass   $(z=0)$  to calculate the ACF–value  $\varphi(k=6)$ ?
What random values  $x_\nu$  are in these memory cells?

$i \ = \ $

$j \ = \ $

2

Which memory cell  ${\rm H}\big[\hspace{0.03cm} i \hspace{0.03cm} \big]$  will be occupied  after the first loop pass   $(z=0)$  with a new random variable  $x_\nu$ ?
Which index   $\nu$  is entered in the process?

$i \ = \ $

$\nu\ =\ $

3

Which memory elements  ${\rm H}\big[\hspace{0.03cm} i \hspace{0.03cm} \big]$  and  ${\rm H}\big[\hspace{0.03cm} j \hspace{0.03cm} \big]$  are used in the loop pass  $z=83$  to calculate the ACF value  $\varphi(k=6)$ ?
What random values are in these memory cells?

$i \ = \ $

$j \ = \ $


Solution

For the exemplary numerical ACF calculation


(1)  With  $z= 0$  and  $k=6$  results according to the program:   $\underline{i= 0}$  and  $\underline{j= 6}$.

  • The corresponding memory contents are  ${\rm H}\big[\hspace{0.03cm} 0 \hspace{0.03cm}\big] = x_1$  and  ${\rm H}\big[\hspace{0.03cm} 6 \hspace{0.03cm}\big] = x_7$.



(2)  In the field  ${\rm H}\big[\hspace{0.03cm} 0 \hspace{0.03cm}\big]$  the random variable  $x_{12}$  is now entered:

$$\text{memory cell }\underline{i= 0},\hspace{1cm}\text{sequence index }\underline{\nu= 12}.$$


(3)  The graph shows the allocation of the auxiliary field with the random values  $x_\nu$.

  • In each case,  the memory cell  ${\rm H}\big[\hspace{0.03cm} i \hspace{0.03cm}\big]$  is highlighted in green.  The new random variable is entered into this memory location at the end of each loop  (line 18).
  • For  $z= 83$  and  $K=6$  this results in
$$\underline{i= 83 \hspace{-0.2cm}\mod \hspace{-0.15cm} \ 11 = 6},\hspace{1cm} \underline{j= (i+k)\hspace{-0.2cm}\mod \hspace{-0.15cm} \ 11 = 1}.$$
  • Loop pass  $z= 83$:   In memory cell  ${\rm H}\big[\hspace{0.03cm} 6 \hspace{0.03cm}\big]$  is the random variable  $x_{84}$  and in the memory cell  ${\rm H}\big[\hspace{0.03cm} 1 \hspace{0.03cm}\big]$  is the random variable  $x_{90}$.
  • At the end of loop pass  $z= 83$  in  ${\rm H}\big[\hspace{0.03cm} 6 \hspace{0.03cm}\big]$:  The content  $x_{84}$  is replaced by  $x_{95}$ .