Difference between revisions of "Aufgaben:Exercise 3.1: Cosine-square PDF and PDF with Dirac Functions"

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{{quiz-Header|Buchseite=Theory_of_Stochastic_Signals/Probability_Density_Function_(PDF)
+
{{quiz-Header|Buchseite=Theory_of_Stochastic_Signals/Probability_Density_Function
 
}}
 
}}
  
[[File:P_ID143__Sto_A_3_1.png|right|frame|Cosine–Square–PDF (top) and Dirac–PDF (bottom)]]
+
[[File:P_ID143__Sto_A_3_1.png|right|frame|Cosine&ndash;square PDF&nbsp; (top),&nbsp; and <br>Dirac delta PDF&nbsp; (bottom)]]
The graph shows the probability density functions (PDF) of two random variables&nbsp; $x$&nbsp; and&nbsp; $y$.
+
The graph shows the probability density functions&nbsp; $\rm (PDF)$&nbsp; of two random variables&nbsp; $x$&nbsp; and&nbsp; $y$.
  
 
*The PDF of the random variable&nbsp; $x$&nbsp; in analytical form is:
 
*The PDF of the random variable&nbsp; $x$&nbsp; in analytical form is:
:$$f_x(x)=\left\{\begin{array}{*{4}{c}}A \cdot \cos^2({\pi}/{4}\cdot x)  &\rm f\ddot{u}r\hspace{0.1cm} -2\le \it x\le \rm +2, \\0 & \rm else.  \\\end{array}\right.$$
+
:$$f_x(x)=\left\{\begin{array}{*{4}{c}}A \cdot \cos^2({\pi}/{4}\cdot x)  &\rm for\hspace{0.1cm} -2\le \it x\le \rm +2, \\0 & \rm else.  \\\end{array}\right.$$
 
 
*The PDF of the random variable&nbsp; $y$&nbsp; consists of a total of five Dirac functions with the weights given in the graph.
 
 
 
 
 
If we consider these random variables as instantaneous values of two random signals&nbsp; $x(t)$&nbsp; and&nbsp; $y(t)$, it is obvious that both signals are "amplitude limited" to the range&nbsp; $\pm 2$&nbsp;. Values larger in absolute value do not occur.
 
  
 +
*The PDF of the random variable&nbsp; $y$&nbsp; consists of a total of five Dirac delta functions with the weights given in the graph.
  
  
 +
If we consider these random variables as instantaneous values of two random signals&nbsp; $x(t)$&nbsp; and&nbsp; $y(t)$, <br>it is obvious that both signals are&nbsp; "amplitude limited"&nbsp; to the range&nbsp; $\pm 2$.&nbsp;.
  
  
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Hints:
 
Hints:
 
*The exercise belongs to the chapter&nbsp; [[Theory_of_Stochastic_Signals/Probability_Density_Function|Probability Density Function]].
 
*The exercise belongs to the chapter&nbsp; [[Theory_of_Stochastic_Signals/Probability_Density_Function|Probability Density Function]].
*Reference is also made to the chapter&nbsp; [[Theory_of_Stochastic_Signals/From_Random_Experiment_to_Random_Variable|From random experiment to random variable]].
+
*Reference is also made to the chapter&nbsp; [[Theory_of_Stochastic_Signals/From_Random_Experiment_to_Random_Variable|From Random Experiment to Random Variable]].
 
 
*The following integral equation holds:  
 
*The following integral equation holds:  
 
:$$\int \cos^{\rm 2}( ax)\, {\rm d}x=\frac{x}{2}+\frac{1}{4 a}\cdot \sin(2 ax).$$
 
:$$\int \cos^{\rm 2}( ax)\, {\rm d}x=\frac{x}{2}+\frac{1}{4 a}\cdot \sin(2 ax).$$
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|type="[]"}
 
|type="[]"}
 
+ The random variable&nbsp; $x$&nbsp; is continuous in value.
 
+ The random variable&nbsp; $x$&nbsp; is continuous in value.
+ The random variable $y$&nbsp; is discrete in value.
+
+ The random variable&nbsp; $y$&nbsp; is discrete in value.
- The randomness of $y$&nbsp; is also discrete in time.
+
- The randomness of&nbsp; $y$&nbsp; is also discrete in time.
+ The PDF says nothing regarding "discrete-time/continuous-time."
+
+ The PDF says nothing regarding&nbsp; "discrete-time/continuous-time."
  
  
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{What is the probability that&nbsp; $x = 0$&nbsp; (exactly) holds?
+
{What is the probability that&nbsp; $x = 0$&nbsp; holds?
 
|type="{}"}
 
|type="{}"}
 
${\rm Pr}(x = 0)\ = \ $ { 0. }
 
${\rm Pr}(x = 0)\ = \ $ { 0. }
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{What is the probability that&nbsp; $y > 0$&nbsp; is?
+
{What is the probability that&nbsp; $y > 0$&nbsp;?
 
|type="{}"}
 
|type="{}"}
 
${\rm Pr}(y > 0)\ = \ $ { 0.3 3% }
 
${\rm Pr}(y > 0)\ = \ $ { 0.3 3% }
  
  
{What is the probability that&nbsp; $y$&nbsp; is smaller than&nbsp; $1$&nbsp; in terms of absolute value?
+
{What is the probability that&nbsp; $|\hspace{0.05cm}y\hspace{0.05cm}|$&nbsp; is smaller than&nbsp; $1$&nbsp;?
 
|type="{}"}
 
|type="{}"}
 
${\rm Pr}(|\hspace{0.05cm}y\hspace{0.05cm}| <1)\ = \ $ { 0.4 3% }
 
${\rm Pr}(|\hspace{0.05cm}y\hspace{0.05cm}| <1)\ = \ $ { 0.4 3% }
  
  
{What is the probability that&nbsp; $x$&nbsp; is smaller than &nbsp; $1$&nbsp; in terms of absolute value?
+
{What is the probability that&nbsp; $|\hspace{0.05cm}x\hspace{0.05cm}|$&nbsp; is smaller than &nbsp; $1$&nbsp;?
 
|type="{}"}
 
|type="{}"}
 
${\rm Pr}(|\hspace{0.05cm}x\hspace{0.05cm}| <1)\ = \ $ { 0.818 3% }
 
${\rm Pr}(|\hspace{0.05cm}x\hspace{0.05cm}| <1)\ = \ $ { 0.818 3% }
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===Solution===
 
===Solution===
 
{{ML-Kopf}}
 
{{ML-Kopf}}
[[File:P_ID174__Sto_A_3_1_b.png|right|frame|For calculating PDF area]]
+
'''(1)'''&nbsp; Correct are&nbsp; <u>statements 1, 2, and 4</u>:
'''(1)'''&nbsp; Correct are <u>statements 1, 2, and 4</u>:
+
* $x$&nbsp; is  continuous in value.
* $x$&nbsp; is  continuous value.
+
* $y$&nbsp; is discrete in value&nbsp; $(M = 5)$.  
* $y$&nbsp; is discrete value&nbsp; $(M = 5)$.  
 
 
*The PDF does not provide information about whether a random variable is discrete or continuous in time.
 
*The PDF does not provide information about whether a random variable is discrete or continuous in time.
  
  
  
'''(2)'''&nbsp; The area under the PDF must&nbsp; yield $1$&nbsp;.
+
[[File:EN_Sto_A_3_1_b.png|right|frame|For calculating the PDF area]]
*By simple geometric &nbsp; reasoning, one arrives at the result $\underline{A=0.5}$.
+
'''(2)'''&nbsp; The area under the PDF must&nbsp; yield $1$:
 +
*By simple geometric reasoning, &nbsp; one arrives at the result $\underline{A=0.5}$.
  
  
  
'''(3)'''&nbsp; The probability that the continuous-valued random variablee&nbsp; $x$&nbsp; takes a fixed value&nbsp; $x_0$&nbsp; is always negligibly small &nbsp; &#8658; &nbsp; $\underline{{\rm Pr}(x = 0) = 0}$.
+
'''(3)'''&nbsp; The probability that the continuous-valued random variable&nbsp; $x$&nbsp; takes a fixed value&nbsp; $x_0$&nbsp; is always negligibly small:
*On the other hand, for the discrete value random variable&nbsp; $y$&nbsp; holds according to the specification: &nbsp; ${\rm Pr}(y = 0) = 0.4$&nbsp; $($weight of the Dirac function at&nbsp; $y = 0)$.
+
:$$\underline{{\rm Pr}(x = 0) = 0}.$$  
 +
*On the other hand,&nbsp; for the discrete value random variable&nbsp; $y$&nbsp; holds according to the specification: &nbsp;  
 +
:$${\rm Pr}(y = 0) = 0.4,$$  
 +
:because the given weight of the Dirac delta function at&nbsp; $y = 0$&nbsp; is&nbsp;$0.4$.
  
  
  
'''(4)'''&nbsp; Because of&nbsp; ${{\rm Pr}(x = 0) = 0}$&nbsp; and PDF symmetry, we get&nbsp; $\underline{{\rm Pr}(x > 0) = 0.5}$.
+
'''(4)'''&nbsp; Because of&nbsp; ${{\rm Pr}(x = 0) = 0}$&nbsp; and the PDF symmetry,&nbsp; we get&nbsp; $\underline{{\rm Pr}(x > 0) = 0.5}$.
  
  
  
'''(5)'''&nbsp; Since&nbsp; $y$&nbsp; is a discrete random variable, the probabilities for&nbsp; $y = 1$&nbsp; and&nbsp; $y = 2$ add up:
+
'''(5)'''&nbsp; Since&nbsp; $y$&nbsp; is a discrete random variable,&nbsp; the probabilities for&nbsp; $y = 1$&nbsp; and&nbsp; $y = 2$&nbsp; add up:
 
:$${\rm Pr}(y >0) = {\rm Pr}(y = 1) + {\rm Pr}( y = 2) \hspace{0.15cm}\underline {= 0.3}.$$
 
:$${\rm Pr}(y >0) = {\rm Pr}(y = 1) + {\rm Pr}( y = 2) \hspace{0.15cm}\underline {= 0.3}.$$
  
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'''(7)'''&nbsp; The probability we are looking for is equal to the integral from&nbsp; $-1$&nbsp; to&nbsp; $+1$&nbsp; over the PDF of the continuous random variable&nbsp; $x$.  
 
'''(7)'''&nbsp; The probability we are looking for is equal to the integral from&nbsp; $-1$&nbsp; to&nbsp; $+1$&nbsp; over the PDF of the continuous random variable&nbsp; $x$.  
*Taking into account the symmetry and the given equation, we obtain:
+
*Taking into account the symmetry and the given equation,&nbsp; we obtain:
 
:$${\rm Pr}(|\hspace{0.05cm} x\hspace{0.05cm}|<1)=2 \cdot \int_{0}^{1}{1}/{2}\cdot \cos^2({\pi}/{4}\cdot x)\hspace{0.1cm}{\rm d}x={x}/{2}+{1}/{\pi}\cdot \sin({\pi}/{2}\cdot x)\Big |_{\rm 0}^{\rm 1}=\rm{1}/{2} + {1}/{\pi}
 
:$${\rm Pr}(|\hspace{0.05cm} x\hspace{0.05cm}|<1)=2 \cdot \int_{0}^{1}{1}/{2}\cdot \cos^2({\pi}/{4}\cdot x)\hspace{0.1cm}{\rm d}x={x}/{2}+{1}/{\pi}\cdot \sin({\pi}/{2}\cdot x)\Big |_{\rm 0}^{\rm 1}=\rm{1}/{2} + {1}/{\pi}
 
\hspace{0.15cm}\underline{
 
\hspace{0.15cm}\underline{

Latest revision as of 17:53, 8 February 2022

Cosine–square PDF  (top),  and
Dirac delta PDF  (bottom)

The graph shows the probability density functions  $\rm (PDF)$  of two random variables  $x$  and  $y$.

  • The PDF of the random variable  $x$  in analytical form is:
$$f_x(x)=\left\{\begin{array}{*{4}{c}}A \cdot \cos^2({\pi}/{4}\cdot x) &\rm for\hspace{0.1cm} -2\le \it x\le \rm +2, \\0 & \rm else. \\\end{array}\right.$$
  • The PDF of the random variable  $y$  consists of a total of five Dirac delta functions with the weights given in the graph.


If we consider these random variables as instantaneous values of two random signals  $x(t)$  and  $y(t)$,
it is obvious that both signals are  "amplitude limited"  to the range  $\pm 2$. .



Hints:

$$\int \cos^{\rm 2}( ax)\, {\rm d}x=\frac{x}{2}+\frac{1}{4 a}\cdot \sin(2 ax).$$


Questions

1

Which of the following statements are absolutely true?

The random variable  $x$  is continuous in value.
The random variable  $y$  is discrete in value.
The randomness of  $y$  is also discrete in time.
The PDF says nothing regarding  "discrete-time/continuous-time."

2

Calculate the parameter  $A$  of the PDF  $f_x(x)$.

$A \ = \ $

3

What is the probability that  $x = 0$  holds?

${\rm Pr}(x = 0)\ = \ $

4

What is the probability that  $x > 0$ ?

${\rm Pr}(x > 0)\ = \ $

5

What is the probability that  $y > 0$ ?

${\rm Pr}(y > 0)\ = \ $

6

What is the probability that  $|\hspace{0.05cm}y\hspace{0.05cm}|$  is smaller than  $1$ ?

${\rm Pr}(|\hspace{0.05cm}y\hspace{0.05cm}| <1)\ = \ $

7

What is the probability that  $|\hspace{0.05cm}x\hspace{0.05cm}|$  is smaller than   $1$ ?

${\rm Pr}(|\hspace{0.05cm}x\hspace{0.05cm}| <1)\ = \ $


Solution

(1)  Correct are  statements 1, 2, and 4:

  • $x$  is continuous in value.
  • $y$  is discrete in value  $(M = 5)$.
  • The PDF does not provide information about whether a random variable is discrete or continuous in time.


For calculating the PDF area

(2)  The area under the PDF must  yield $1$:

  • By simple geometric reasoning,   one arrives at the result $\underline{A=0.5}$.


(3)  The probability that the continuous-valued random variable  $x$  takes a fixed value  $x_0$  is always negligibly small:

$$\underline{{\rm Pr}(x = 0) = 0}.$$
  • On the other hand,  for the discrete value random variable  $y$  holds according to the specification:  
$${\rm Pr}(y = 0) = 0.4,$$
because the given weight of the Dirac delta function at  $y = 0$  is $0.4$.


(4)  Because of  ${{\rm Pr}(x = 0) = 0}$  and the PDF symmetry,  we get  $\underline{{\rm Pr}(x > 0) = 0.5}$.


(5)  Since  $y$  is a discrete random variable,  the probabilities for  $y = 1$  and  $y = 2$  add up:

$${\rm Pr}(y >0) = {\rm Pr}(y = 1) + {\rm Pr}( y = 2) \hspace{0.15cm}\underline {= 0.3}.$$


(6)  The event  $|\hspace{0.05cm} y \hspace{0.05cm} | < 1$  here is identical to  $y = 0$. Thus we obtain:

$${\rm Pr}(|\hspace{0.05cm}y\hspace{0.05cm}| < 1) = {\rm Pr}( y = 0)\hspace{0.15cm}\underline { = 0.4}.$$


(7)  The probability we are looking for is equal to the integral from  $-1$  to  $+1$  over the PDF of the continuous random variable  $x$.

  • Taking into account the symmetry and the given equation,  we obtain:
$${\rm Pr}(|\hspace{0.05cm} x\hspace{0.05cm}|<1)=2 \cdot \int_{0}^{1}{1}/{2}\cdot \cos^2({\pi}/{4}\cdot x)\hspace{0.1cm}{\rm d}x={x}/{2}+{1}/{\pi}\cdot \sin({\pi}/{2}\cdot x)\Big |_{\rm 0}^{\rm 1}=\rm{1}/{2} + {1}/{\pi} \hspace{0.15cm}\underline{ \approx 0.818}.$$