[[File:P_ID423__Sto_Z_4_7.png|right|frame|Requirements for the generation of a <br>2D random variable]]
[[File:P_ID423__Sto_Z_4_7.png|right|frame|Requirements for the generation of a <br>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 2D random variable $(x, y)$ where for the components:
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:
:$$x = A \cdot u + B \cdot v + C,$$
:$$x = A \cdot u + B \cdot v + C,$$
:$$y= D \cdot u + E \cdot v + F.$$
:$$y= D \cdot u + E \cdot v + F.$$
The 2D–random variable $(x, y)$ to be generated should have the following statistical properties:
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 variances be $\sigma_x^2 = 4$ and $\sigma_y^2 = 10$.
* Let the random variable $x$ be mean-free $(m_x =0)$.
* Let the random variable $x$ be mean-free $(m_x =0)$.
* For the mean of $y$ let $m_y = 1$ hold.
* For the mean of $y$ let $m_y = 1$ hold.
* The random variable $x$ possess a triangular PDF $f_x(x)$ corresponding to the above graph.
* The random variable $x$ possess a triangular PDF $f_x(x)$ corresponding to the above graph.
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Hints:
''Hints:''
*The exercise belongs to the chapter [[Theory_of_Stochastic_Signals/Linear_Combinations_of_Random_Variables|Linear Combinations of Random Variables]].
*The exercise belongs to the chapter [[Theory_of_Stochastic_Signals/Linear_Combinations_of_Random_Variables|Linear Combinations of Random Variables]].
*In particular, reference is made to the page [Theory_of_Stochastic_Signals/Linear_Combinations_of_Random_Variables#Generation_of_correlated_random_variables|Generation of correlated random variables]].
*In particular, reference is made to the page [[Theory_of_Stochastic_Signals/Linear_Combinations_of_Random_Variables#Generation_of_correlated_random_variables|Generation of correlated random variables]].
*To avoid ambiguity, it is specified that all coefficients $A$, ... , $F$ should be non-negative.
*To avoid ambiguity, it is specified that all coefficients $A$, ... , $F$ should be non-negative.
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{Determine the coefficients $D$ and $E$, where $D > E$ should hold.
{Determine the coefficients $D$ and $E$, where $D > E$ should hold.
|type="{}"}
|type="{}"}
$D \ = \ $ { 3.464 3% }
$D \ = \ $ { 3.464 3% }
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{Specify the maximum values for $x$ and $y$ .
{Specify the maximum values for $x$ and $y$.
|type="{}"}
|type="{}"}
$x_\text{max}\ = \ $ { 3.464 3% }
$x_\text{max}\ = \ $ { 3.464 3% }
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===Solution===
===Solution===
{{ML-Kopf}}
{{ML-Kopf}}
'''(1)''' Given the mean values given, it must hold:
'''(1)''' Given the mean values, it must hold:
'''(3)''' With $ A = B = \sqrt{3}$ corresponding to the last subtask, two equations of determination remain for $D$ and $E$:
'''(3)''' With $ A = B = \sqrt{3}$ corresponding to the last subtask, two equations of determination remain for $D$ and $E$:
'''(4)''' The random variables $x$ and $y$ respectively, take their maximum values when respectively $u= +1$ and $v= +1$ holds:
'''(4)''' The random variables $x$ and $y$ resp. take their maximum values when $u= +1$ and $v= +1$ holds: