Difference between revisions of "Aufgaben:Exercise 4.7Z: Generation of a Joint PDF"

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{{quiz-Header|Buchseite=Theory_of_Stochastic_Signals/Linear_Combinations_of_Random_Variables
 
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[[File:P_ID423__Sto_Z_4_7.png|right|]]
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[[File:P_ID423__Sto_Z_4_7.png|right|frame|Requirements for the generation of a <br>two-dimensional random variable]]
:Ausgehend von statistisch unabh&auml;ngigen Gr&ouml;&szlig;en <i>u</i> und <i>&upsilon;</i>, die beide zwischen &ndash;1 und +1 gleichverteilt sind und somit jeweils die Varianz <i>&sigma;</i><sup>2</sup> = 2/3 besitzen, soll eine 2D-Zufallsgr&ouml;&szlig;e (<i>x</i>, <i>y</i>) generiert werden, wobei f&uuml;r die Komponenten gilt:
+
Given statistically independent quantities&nbsp; $u$&nbsp; and&nbsp; $v$,
:$$x = A \cdot u + B \cdot  v + C,$$
+
*both of which are uniformly distributed between&nbsp; $-1$&nbsp; and&nbsp; $+1$,&nbsp; and
:$$y= D \cdot u + E \cdot  v + F.$$
+
*thus each have variance&nbsp; $\sigma^2 = 2/3$,&nbsp;  
  
:Die zu erzeugende 2D&ndash;Zufallsgr&ouml;&szlig;e (<i>x</i>, <i>y</i>) soll die folgenden statistischen Eigenschaften aufweisen:
 
  
:* Die Varianzen seien <i>&sigma;<sub>x</sub></i><sup>2</sup> = 4 und <i>&sigma;<sub>y</sub></i><sup>2</sup> = 10.
+
generate a two-dimensional random variable&nbsp; $(x,\hspace{0.08cm} y)$&nbsp; where for the components:
 +
:$$x = A \cdot u + B \cdot v + C,$$
 +
:$$y= D \cdot u + E \cdot v + F.$$
  
:* Die Zufallsgr&ouml;&szlig;e <i>x</i> sei mittelwertfrei.
+
The two-dimensional random variable&nbsp; $(x,\hspace{0.08cm} y)$&nbsp; to be generated should have the following statistical properties:
 +
* Let the variances be&nbsp; $\sigma_x^2 = 4$&nbsp; and&nbsp; $\sigma_y^2 = 10$.
 +
* Let the random variable&nbsp; $x$&nbsp; be mean-free&nbsp; $(m_x =0)$.
 +
* For the mean of&nbsp; $y$&nbsp; let&nbsp; $m_y = 1$&nbsp; hold.
 +
* The correlation coefficient between&nbsp; $x$&nbsp; and&nbsp; $y$&nbsp; is&nbsp; $\rho_{xy} = \sqrt{0.9} = 0.949.$
 +
* The random variable&nbsp; $x$&nbsp; possess a triangular PDF $f_x(x)$&nbsp; corresponding to the above graph.
 +
* The random variable&nbsp; $y$&nbsp; has a trapezoidal PDF $f_y(y)$&nbsp; according to the lower graph.
  
:* F&uuml;r den Mittelwert von <i>y</i> gelte <i>m<sub>y</sub></i> = 1.
 
  
:* Der Korrelationskoeffizient zwischen <i>x</i> und <i>y</i> betrage
 
:$$\rho_{xy} = \sqrt{0.9} = 0.949.$$
 
  
:* Die Zufallsgr&ouml;&szlig;e <i>x</i> besitze eine dreieckf&ouml;rmige WDF  <i>f<sub>x</sub></i>(<i>x</i>) entsprechend der oberen Grafik.
 
  
:* Die Zufallsgr&ouml;&szlig;e <i>y</i> besitze eine trapezf&ouml;rmige WDF <i>f<sub>y</sub></i>(<i>y</i>) entsprechend der unteren Grafik.
+
Hints:  
 +
*The exercise belongs to the chapter&nbsp; [[Theory_of_Stochastic_Signals/Linear_Combinations_of_Random_Variables|Linear Combinations of Random Variables]].
 +
*In particular,&nbsp; reference is made to the page&nbsp; [[Theory_of_Stochastic_Signals/Linear_Combinations_of_Random_Variables#Generation_of_correlated_random_variables|Generation of correlated random variables]].
 +
*To avoid ambiguity,&nbsp; it is specified that all coefficients&nbsp; $A$, ... , $F$&nbsp; should be non-negative.
 +
   
  
:<b>Hinweis:</b>&nbsp;Diese Aufgabe bezieht sich auf den Theorieteil von Kapitel 4.3. Um Mehrdeutigkeiten zu vermeiden wird festgelegt, dass alle Koeffizienten <i>A</i> ... <i>F</i> nicht negativ sein sollen.
 
  
 
+
===Questions===
===Fragebogen===
 
  
 
<quiz display=simple>
 
<quiz display=simple>
{Bestimmen Sie die Koeffizienten <i>C</i> und <i>F</i>.
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{Determine the coefficients&nbsp; $C$&nbsp; and&nbsp; $F$.
 
|type="{}"}
 
|type="{}"}
$C$ = { 0 3% }
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$C \ = \ $ { 0. }
$F$ = { 1 3% }
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$F\ = \ $ { 1 3% }
  
  
{Bestimmen Sie die Koeffizienten <i>A</i> und <i>B</i>.
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{Determine the coefficients&nbsp; $A$&nbsp; and&nbsp; $B$.
 
|type="{}"}
 
|type="{}"}
$A$ = { 1.732 3% }
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$A \ = \ $ { 1.732 3% }
$B$ = { 1.732 3% }
+
$B \ = \ $ { 1.732 3% }
  
  
{Bestimmen Sie die Koeffizienten <i>D</i> und <i>E</i>, wobei <i>D</i> > <i>E</i> gelten soll.
+
{Determine the coefficients&nbsp; $D$&nbsp; and&nbsp; $E$,&nbsp; where&nbsp; $D > E$&nbsp; should hold.
 
|type="{}"}
 
|type="{}"}
$D$ = { 3.464 3% }
+
$D \ = \ $ { 3.464 3% }
$E$ = { 1.732 3% }
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$E \ = \ $ { 1.732 3% }
  
  
{Geben Sie die Maximalwerte f&uuml;r <i>x</i> und <i>y</i> an.
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{Specify the maximum values for&nbsp; $x$&nbsp; and&nbsp; $y$.
 
|type="{}"}
 
|type="{}"}
$x_\text{max}$ = { 3.464 3% }
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$x_\text{max}\ = \ $ { 3.464 3% }
$y_\text{max}$ = { 6.196 3% }
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$y_\text{max}\ = \ $ { 6.196 3% }
 +
 
  
  
 
</quiz>
 
</quiz>
  
===Musterlösung===
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===Solution===
 
{{ML-Kopf}}
 
{{ML-Kopf}}
:<b>1.</b>&nbsp;&nbsp;Aufgrund der angegebenen Mittelwerte muss gelten: <u><i>C</i> = <i>m<sub>x</sub></i> = 0</u> und <u><i>F</i> = <i>m<sub>y</sub></i> = 1</u>.
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'''(1)'''&nbsp; Given the mean values,&nbsp; it must hold:
 +
:$$ C = m_x\hspace{0.15cm}\underline{ = 0},$$
 +
:$$ F = m_y\hspace{0.15cm}\underline{ = 1}.$$
 +
 
  
:<b>2.</b>&nbsp;&nbsp;Unter Ber&uuml;cksichtigung von <i>&sigma;</i><sup>2</sup> = 2/3 gilt:
+
'''(2)'''&nbsp; Taking into account&nbsp; $\sigma^2 = 2/3$&nbsp; holds:
:$$\sigma_x^2 = \sigma^2 \cdot ( A^2 + B^2)= \frac {2}{3} \cdot ( A^2 + B^2) .$$
+
:$$\sigma_x^2 = \sigma^2 \cdot ( A^2 + B^2)= {2}/{3} \cdot ( A^2 + B^2) .$$
  
:Wegen <i>&sigma;<sub>x</sub></i><sup>2</sup> = 4 folgt daraus <i>A</i><sup>2</sup> + <i>B</i><sup>2</sup> = 6. Eine dreieckf&ouml;rmige WDF bedeutet, dass <i>A</i> = &plusmn;<i>B</i> gelten muss. Somit erh&auml;lt man <u><i>A</i> = <i>B</i> =</u> 3<sup>1/2</sup> <u>= 1.732</u> (negative Koeffizienten wurden ausgeschlossen).
+
*Because of&nbsp; $\sigma_x^2 = 4$&nbsp; it follows&nbsp; $A^2 + B^2= 6$.  
 +
*A triangular PDF means that&nbsp; $A = \pm B$&nbsp; must hold.  
 +
*Thus,&nbsp; since negative coefficients have been excluded,&nbsp; we obtain:
 +
:$$ A = B = \sqrt{3}\hspace{0.15cm}\underline{ = 1.732}.$$
  
:<b>3.</b>&nbsp;&nbsp;Mit <i>A</i> und <i>B</i> entsprechend Punkt b) verbleiben zwei Bestimmungsgleichungen f&uuml;r <i>D</i> und <i>E</i>:
+
:$$\sigma_y^2 = \sigma^2 \cdot ( D^2 + E^2)= 10 \hspace{0.5cm} \Rightarrow \hspace{0.5cm} D^2 + E^2 = \frac {\sigma_y^2}{\sigma^2} = \frac {10}{2/3} \stackrel{!}{=}15,$$
+
[[File:P_ID424__Sto_Z_4_7_d.png|right|frame|Rhombic joint PDF]]
:$$\rho_{xy} = \frac{A \cdot D + B \cdot E}{\sqrt{(A^2 + B^2)(D^2 + E^2)}} = \frac{\sqrt{3} \cdot (D + E)}{\sqrt{6 \cdot (D^2 + E^2)}}  \stackrel{!}{=} \sqrt{0.9}.$$
+
'''(3)'''&nbsp; With&nbsp; $ A = B = \sqrt{3}$&nbsp; corresponding to the last subtask,&nbsp; two equations of determination remain for&nbsp; $D$&nbsp; and&nbsp; $E$:
[[File:P_ID424__Sto_Z_4_7_d.png|right|]]
+
:$$\sigma_y^2 = \sigma^2 \cdot ( D^2 + E^2)= 10 \hspace{0.5cm} \Rightarrow \hspace{0.5cm} D^2 + E^2 = \frac {\sigma_y^2}{\sigma^2} = \frac {10}{2/3} \stackrel{!}{=}15,$$
 +
:$$\rho_{xy} = \frac{A \cdot D + B \cdot E}{\sqrt{(A^2 + B^2)(D^2 + E^2)}} = \frac{\sqrt{3} \cdot (D + E)}{\sqrt{6 \cdot (D^2 + E^2)}}  \stackrel{!}{=} \sqrt{0.9}.$$
  
:Daraus folgt weiter:
+
*From this it further follows:&nbsp; $D + E = \sqrt{1.8 \cdot ( D^2 + E^2)} = \sqrt{27} = 3 \cdot \sqrt{3}.$
:$$D + E = \sqrt{1.8 \cdot ( D^2 + E^2)} = \sqrt{27} = 3 \sqrt{3}.$$
+
*The equation,&nbsp; in conjunction with&nbsp; $D^2 + E^2 = 15$&nbsp; and the constraint&nbsp; $(D>E)$&nbsp; leads to the result:
 +
:$$ D= 2 \cdot \sqrt{3}\hspace{0.15cm}\underline{ = 3.464}, \hspace{0.5cm}E= \sqrt{3} \hspace{0.15cm}\underline{= 1.732}.$$
  
:Die Gleichung führt in Verbindung mit <i>D</i><sup>2</sup> + <i>E</i><sup>2</sup> = 15 und der oben angegebenen Nebenbedingung (<i>D</i> > <i>E</i>) zum Ergebnis:
 
:$$ D= 2 \sqrt{3}\hspace{0.15cm}\underline{ = 3.464}, \hspace{0.5cm}E= \sqrt{3} \hspace{0.15cm}\underline{= 1.732}.$$
 
  
:<b>4.</b>&nbsp;&nbsp;Mit <i>A</i> = <i>B</i> = 1.732 kann die Zufallsgr&ouml;&szlig;e <u><i>x</i> maximal den Wert 3.464</u> annehmen (wenn jeweils <i>u</i> = 1 und <i>&upsilon;</i> = 1 gilt).
+
'''(4)'''&nbsp; The random variables&nbsp; $x$&nbsp; and&nbsp; $y$&nbsp; resp. take their maximum values when&nbsp; $u= +1$ and&nbsp; $v= +1$&nbsp; holds:
 +
:$$ x_\text{max}= A+B \hspace{0.15cm}\underline{ = +3.464}, \hspace{0.5cm} x_\text{min} = - A - B= -3.464.$$
 +
:$$ y_\text{max}= D+E+F \hspace{0.15cm}\underline{ = +6.196}, \hspace{0.5cm} y_\text{min} = -D-E+F= -4.196.$$
  
:Das Maximum von <i>y</i> ergibt sich mit diesen Parameterwerten zu <u><i>y</i><sub>max</sub> =</u> <i>D</i> + <i>E</i> + <i>F</i> <u>= 6.196</u>, der Minimalwert zu <i>y</i><sub>min</sub> = &ndash;<i>D</i> &ndash;<i>E</i> +<i>F</i> = &ndash;4.196 (siehe Skizze der 2D-WDF).
 
<br><br><br><br>
 
 
{{ML-Fuß}}
 
{{ML-Fuß}}
  
  
  
[[Category:Aufgaben zu Stochastische Signaltheorie|^4.3 Linearkombinationen von Zufallsgrößen^]]
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[[Category:Theory of Stochastic Signals: Exercises|^4.3 Linear Combinations^]]

Latest revision as of 18:45, 25 February 2022

Requirements for the generation of a
two-dimensional random variable

Given statistically independent quantities  $u$  and  $v$,

  • both of which are uniformly distributed between  $-1$  and  $+1$,  and
  • thus each have variance  $\sigma^2 = 2/3$, 


generate a two-dimensional random variable  $(x,\hspace{0.08cm} y)$  where for the components:

$$x = A \cdot u + B \cdot v + C,$$
$$y= D \cdot u + E \cdot v + F.$$

The two-dimensional random variable  $(x,\hspace{0.08cm} y)$  to be generated should have the following statistical properties:

  • Let the variances be  $\sigma_x^2 = 4$  and  $\sigma_y^2 = 10$.
  • Let the random variable  $x$  be mean-free  $(m_x =0)$.
  • For the mean of  $y$  let  $m_y = 1$  hold.
  • The correlation coefficient between  $x$  and  $y$  is  $\rho_{xy} = \sqrt{0.9} = 0.949.$
  • The random variable  $x$  possess a triangular PDF $f_x(x)$  corresponding to the above graph.
  • The random variable  $y$  has a trapezoidal PDF $f_y(y)$  according to the lower graph.



Hints:


Questions

1

Determine the coefficients  $C$  and  $F$.

$C \ = \ $

$F\ = \ $

2

Determine the coefficients  $A$  and  $B$.

$A \ = \ $

$B \ = \ $

3

Determine the coefficients  $D$  and  $E$,  where  $D > E$  should hold.

$D \ = \ $

$E \ = \ $

4

Specify the maximum values for  $x$  and  $y$.

$x_\text{max}\ = \ $

$y_\text{max}\ = \ $


Solution

(1)  Given the mean values,  it must hold:

$$ C = m_x\hspace{0.15cm}\underline{ = 0},$$
$$ F = m_y\hspace{0.15cm}\underline{ = 1}.$$


(2)  Taking into account  $\sigma^2 = 2/3$  holds:

$$\sigma_x^2 = \sigma^2 \cdot ( A^2 + B^2)= {2}/{3} \cdot ( A^2 + B^2) .$$
  • Because of  $\sigma_x^2 = 4$  it follows  $A^2 + B^2= 6$.
  • A triangular PDF means that  $A = \pm B$  must hold.
  • Thus,  since negative coefficients have been excluded,  we obtain:
$$ A = B = \sqrt{3}\hspace{0.15cm}\underline{ = 1.732}.$$


Rhombic joint PDF

(3)  With  $ A = B = \sqrt{3}$  corresponding to the last subtask,  two equations of determination remain for  $D$  and  $E$:

$$\sigma_y^2 = \sigma^2 \cdot ( D^2 + E^2)= 10 \hspace{0.5cm} \Rightarrow \hspace{0.5cm} D^2 + E^2 = \frac {\sigma_y^2}{\sigma^2} = \frac {10}{2/3} \stackrel{!}{=}15,$$
$$\rho_{xy} = \frac{A \cdot D + B \cdot E}{\sqrt{(A^2 + B^2)(D^2 + E^2)}} = \frac{\sqrt{3} \cdot (D + E)}{\sqrt{6 \cdot (D^2 + E^2)}} \stackrel{!}{=} \sqrt{0.9}.$$
  • From this it further follows:  $D + E = \sqrt{1.8 \cdot ( D^2 + E^2)} = \sqrt{27} = 3 \cdot \sqrt{3}.$
  • The equation,  in conjunction with  $D^2 + E^2 = 15$  and the constraint  $(D>E)$  leads to the result:
$$ D= 2 \cdot \sqrt{3}\hspace{0.15cm}\underline{ = 3.464}, \hspace{0.5cm}E= \sqrt{3} \hspace{0.15cm}\underline{= 1.732}.$$


(4)  The random variables  $x$  and  $y$  resp. take their maximum values when  $u= +1$ and  $v= +1$  holds:

$$ x_\text{max}= A+B \hspace{0.15cm}\underline{ = +3.464}, \hspace{0.5cm} x_\text{min} = - A - B= -3.464.$$
$$ y_\text{max}= D+E+F \hspace{0.15cm}\underline{ = +6.196}, \hspace{0.5cm} y_\text{min} = -D-E+F= -4.196.$$