Difference between revisions of "Aufgaben:Exercise 2.1Z: Different Signal Courses"

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{{quiz-Header|Buchseite=Stochastische Signaltheorie/Wahrscheinlichkeit und relative Häufigkeit
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{{quiz-Header|Buchseite=Theory_of_Stochastic_Signals/From_Random_Experiment_to_Random_Variable
 
}}
 
}}
  
[[File:P_ID59__Sto_Z_2_1.png|right|frame|Discrete value or continuous value?]]
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[[File:P_ID59__Sto_Z_2_1.png|right|frame|Discrete-value or continuous-value?]]
On the right are shown five signals.  The first three signals  $\rm (A)$,  $\rm (B)$  and  $\rm (C)$  are periodic and thus also deterministic, the two lower signals have stochastic character. The current value of these signals  $x(t)$  is taken as a random quantity in each case.
+
On the right are shown five signals.  The first three signals  $\rm (A)$,  $\rm (B)$  and  $\rm (C)$  are periodic and thus also deterministic,  the two lower signals have stochastic character.  The current value of these signals  $x(t)$  is taken as a random variable in each case.
  
 
Shown in detail are:
 
Shown in detail are:
  
$\rm (A)$:   a triangular-shaped periodic signal,
+
$\rm (A)$:   A triangular-shaped periodic signal,
  
 
$\rm (B)$:   the signal  $\rm (A)$  after one-way rectification,
 
$\rm (B)$:   the signal  $\rm (A)$  after one-way rectification,
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$\rm (D)$:   a rectangular random signal,
 
$\rm (D)$:   a rectangular random signal,
  
$\rm (E)$: &nbsp;&nbsp;the random signal&nbsp; $\rm (D)$&nbsp; according to &nbsp;AMI coding; &nbsp; <br>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; here the "zero" is preserved, while each "one" is alternately encoded with "$+2\hspace{0.03cm}\rm V$" and "$-2\hspace{0.03cm} \rm V$".
+
$\rm (E)$: &nbsp;&nbsp;the random signal&nbsp; $\rm (D)$&nbsp; according to &nbsp;AMI coding; &nbsp; <br>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; here the&nbsp; "zero"&nbsp; is preserved,&nbsp; while each&nbsp; "one" is&nbsp; alternately encoded with&nbsp; $+2\hspace{0.03cm}\rm V$&nbsp; and&nbsp; $-2\hspace{0.03cm} \rm V$.
  
  
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<quiz display=simple>
 
<quiz display=simple>
{For which signals does the current value describe a discrete random variable? <br>Consider also the respective number of steps&nbsp; $M$.
+
{For which signals does the current value describe a discrete random variable? <br>Consider also the respective number of steps &nbsp; &rArr; &nbsp; $M$.
 
|type="[]"}
 
|type="[]"}
 
- Signal $\rm (A)$,
 
- Signal $\rm (A)$,
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{For which signals is the current value (exclusively) a continuous random variable?  
+
{For which signals is the current value&nbsp; (exclusively)&nbsp; a continuous random variable?  
 
|type="[]"}
 
|type="[]"}
+ signal $\rm (A)$,
+
+ Signal $\rm (A)$,
 
- signal $\rm (B)$,
 
- signal $\rm (B)$,
 
- signal $\rm (C)$,
 
- signal $\rm (C)$,
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{For the signal&nbsp; $\rm (D)$&nbsp; the relative frequency&nbsp; $h_0$&nbsp; is determined empirically over $100\hspace{0.03cm}000$ binary symbols. <br>Name a lower bound for the probability that the determined value lies between&nbsp; $0.49$&nbsp; and&nbsp; $0.51$&nbsp;?
 
{For the signal&nbsp; $\rm (D)$&nbsp; the relative frequency&nbsp; $h_0$&nbsp; is determined empirically over $100\hspace{0.03cm}000$ binary symbols. <br>Name a lower bound for the probability that the determined value lies between&nbsp; $0.49$&nbsp; and&nbsp; $0.51$&nbsp;?
 
|type="{}"}
 
|type="{}"}
${\rm Min\big[\ Pr(0.49}≤h_0≤0.51)\ \big] \ = \ $ { 0.975 3% }
+
${\rm Min\big[\ Pr(0.49}≤h_0≤0.51)\ \big] \ = \ $ { 97.5 3% } &nbsp; $\%$
  
  
{How many symbols&nbsp; $(N_\min)$&nbsp; would you need to use for this investigation to ensure <br>that the probability for the event "The frequency so determined is between&nbsp; $0.499$&nbsp; and&nbsp; $0.501$" is greater than&nbsp; $99\%$&nbsp;?
+
{How many symbols&nbsp; $(N_\min)$&nbsp; would you need to use for this investigation to ensure <br>that the probability for the event&nbsp; "The frequency so determined is between&nbsp; $0.499$&nbsp; and&nbsp; $0.501$"&nbsp; is greater than&nbsp; $99\%$&nbsp;?
 
|type="{}"}
 
|type="{}"}
 
$N_\min \ = \ $ { 2.5 3% } $\ \cdot 10^9$
 
$N_\min \ = \ $ { 2.5 3% } $\ \cdot 10^9$
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===Solution===
 
===Solution===
 
{{ML-Kopf}}
 
{{ML-Kopf}}
'''(1)'''&nbsp; Richtig sind die <u>Lösungsvorschläge 3, 4 und 5</u>:
+
'''(1)'''&nbsp; Correct are&nbsp; <u>suggested solutions 3, 4, and 5</u>:
*Die Zufallsgrößen&nbsp; $\rm (C)$&nbsp; und&nbsp; $\rm (D)$&nbsp; sind binär&nbsp; $(M= 2)$,  
+
*The random variables&nbsp; $\rm (C)$&nbsp; and&nbsp; $\rm (D)$&nbsp; are binary&nbsp; $(M= 2)$,  
*w&auml;hrend die Zufallsgr&ouml;&szlig;e&nbsp; $\rm (E)$&nbsp; dreiwertig ist &nbsp; $(M= 3)$.  
+
*while the random variable&nbsp; $\rm (E)$&nbsp; is trivalent&nbsp; $(M= 3)$.  
  
  
  
'''(2)'''&nbsp; Richtig ist allein der <u>Lösungsvorschlag 1</u>:
+
'''(2)'''&nbsp; The&nbsp; <u>proposed solution 1</u>&nbsp; alone is correct:
*Die Zufallsgr&ouml;&szlig;e&nbsp; $\rm (A)$&nbsp; ist wertkontinuierlich und kann alle Werte zwischen&nbsp; $\pm 2 \hspace{0.03cm} \rm V$&nbsp; mit gleicher Wahrscheinlichkeit annehmen.  
+
*The random variable&nbsp; $\rm (A)$&nbsp; is continuous in value and can take all values between&nbsp; $\pm 2 \hspace{0.03cm} \rm V$&nbsp; with equal probability.  
*Alle anderen Zufallsgrößen sind wertdiskret.
+
*All other random variables are discrete in value.
  
  
  
'''(3)'''&nbsp; Richtig ist allein der <u>Lösungsvorschlag 2</u>:
+
'''(3)'''&nbsp; The&nbsp; <u>proposed solution 2</u>&nbsp; alone is correct:
*Nur die Zufallsgr&ouml;&szlig;e&nbsp; $\rm (B)$&nbsp; hat einen diskreten Anteil bei&nbsp; $0\hspace{0.03cm}\rm V$ und
+
*Only the random variable&nbsp; $\rm (B)$&nbsp; has a discrete part at&nbsp; $0\hspace{0.03cm}\rm V$,&nbsp; and
*au&szlig;erdem noch eine kontinuierliche Komponente&nbsp; (zwischen&nbsp; $0\hspace{0.03cm} \rm V$&nbsp; und&nbsp; $+2\hspace{0.03cm}\rm V)$.
+
*also has a continuous component&nbsp; (between&nbsp; $0\hspace{0.03cm} \rm V$&nbsp; and&nbsp; $+2\hspace{0.03cm}\rm V)$.
  
  
'''(4)'''&nbsp; Nach dem Bernoullischen Gesetz der gro&szlig;en Zahlen gilt:
+
'''(4)'''&nbsp; According to Bernoulli's law of large numbers:
 
:$$\rm Pr\left(|\it h_{\rm 0} - \it p_{\rm 0}|\ge\it\varepsilon\right)\le\frac{\rm 1}{\rm 4\cdot \it N\cdot\it\varepsilon^{\rm 2}} = {\it p}_{\rm \hspace{0.01cm}Bernouilli}.$$
 
:$$\rm Pr\left(|\it h_{\rm 0} - \it p_{\rm 0}|\ge\it\varepsilon\right)\le\frac{\rm 1}{\rm 4\cdot \it N\cdot\it\varepsilon^{\rm 2}} = {\it p}_{\rm \hspace{0.01cm}Bernouilli}.$$
  
*Damit ist die Wahrscheinlichkeit, dass die relative H&auml;ufigkeit $h_0$ von der Wahrscheinlichkeit $p_0 = 0.5$ betragsm&auml;&szlig;ig um mehr als $0.01$ abweicht, mit $\varepsilon = 0.01$ berechenbar:
+
*Thus,&nbsp; the probability that the relative frequency&nbsp; $h_0$&nbsp; deviates from the probability&nbsp; $p_0 = 0.5$&nbsp; by more than&nbsp; $0.01$&nbsp; can be calculated as&nbsp; $\varepsilon = 0.01$:
 
:$${\it p}_{\rm \hspace{0.01cm}Bernoulli} = \rm\frac{1}{4\cdot 100000\cdot 0.01^2}=\rm 2.5\% \hspace{0.5cm}\Rightarrow \hspace{0.5cm}
 
:$${\it p}_{\rm \hspace{0.01cm}Bernoulli} = \rm\frac{1}{4\cdot 100000\cdot 0.01^2}=\rm 2.5\% \hspace{0.5cm}\Rightarrow \hspace{0.5cm}
{\rm Min}\big[({\rm Pr}(0.49 \le h_0 \le 0.51)\big] \hspace{0.15cm}\underline{= 0.975}.$$
+
{\rm Min}\big[({\rm Pr}(0.49 \le h_0 \le 0.51)\big] \hspace{0.15cm}\underline{= 97.5\%}.$$
  
  
  
'''(5)'''&nbsp; Mit&nbsp; $p_{\rm Bernoulli} = 1 - 0.99 = 0.01$&nbsp; und&nbsp; $\varepsilon = 0.001$&nbsp; gilt wiederum nach dem Gesetz der gro&szlig;en Zahlen:
+
'''(5)'''&nbsp; With&nbsp; $p_{\rm Bernoulli} = 1 - 0.99 = 0.01$&nbsp; and&nbsp; $\varepsilon = 0.001$&nbsp; holds again by the law of large numbers:
:$${\it p}_{\rm \hspace{0.01cm}Bernoulli}\le\frac{\rm 1}{\rm 4\cdot \it N\cdot\it \varepsilon^{\rm 2}}.$$
+
:$${\it p}_{\rm \hspace{0.01cm}Bernoulli}\le\frac{\rm 1}{\rm 4\cdot \it N\cdot\it \varepsilon^{\rm 2}}.$$
*Aufgel&ouml;st nach&nbsp; $N$&nbsp; erh&auml;lt man:
+
*Solved for&nbsp; $N$,&nbsp; one gets:
:$$N\ge\frac{\rm 1}{\rm 4\cdot\it p_{\rm \hspace{0.01cm}Bernoulli}\cdot\it\varepsilon^{\rm 2}}=\rm \frac{1}{4\cdot 0.01\cdot 0.001^{2}}=\rm 0.25\cdot 10^8
+
:$$N\ge\frac{\rm 1}{\rm 4\cdot\it p_{\rm \hspace{0.01cm}Bernoulli}\cdot\varepsilon^{\rm 2}}=\rm \frac{1}{4\cdot 0.01\cdot 0.001^{2}}=\rm 0.25\cdot 10^8
 
\hspace{0.5cm}\Rightarrow \hspace{0.5cm}
 
\hspace{0.5cm}\Rightarrow \hspace{0.5cm}
 
{\it N}_{\rm min} \hspace{0.15cm}\underline{= 2.5\cdot 10^9}.$$
 
{\it N}_{\rm min} \hspace{0.15cm}\underline{= 2.5\cdot 10^9}.$$

Latest revision as of 14:02, 3 December 2021

Discrete-value or continuous-value?

On the right are shown five signals.  The first three signals  $\rm (A)$,  $\rm (B)$  and  $\rm (C)$  are periodic and thus also deterministic,  the two lower signals have stochastic character.  The current value of these signals  $x(t)$  is taken as a random variable in each case.

Shown in detail are:

$\rm (A)$:   A triangular-shaped periodic signal,

$\rm (B)$:   the signal  $\rm (A)$  after one-way rectification,

$\rm (C)$:   a rectangular periodic signal,

$\rm (D)$:   a rectangular random signal,

$\rm (E)$:   the random signal  $\rm (D)$  according to  AMI coding;  
          here the  "zero"  is preserved,  while each  "one" is  alternately encoded with  $+2\hspace{0.03cm}\rm V$  and  $-2\hspace{0.03cm} \rm V$.




Hints:



Questions

1

For which signals does the current value describe a discrete random variable?
Consider also the respective number of steps   ⇒   $M$.

Signal $\rm (A)$,
signal $\rm (B)$,
signal $\rm (C)$,
signal $\rm (D)$,
signal $\rm (E)$.

2

For which signals is the current value  (exclusively)  a continuous random variable?

Signal $\rm (A)$,
signal $\rm (B)$,
signal $\rm (C)$,
signal $\rm (D)$,
signal $\rm (E)$.

3

Which random variables have a discrete and a continuous part?

Signal $\rm (A)$,
signal $\rm (B)$,
signal $\rm (C)$,
signal $\rm (D)$,
signal $\rm (E)$.

4

For the signal  $\rm (D)$  the relative frequency  $h_0$  is determined empirically over $100\hspace{0.03cm}000$ binary symbols.
Name a lower bound for the probability that the determined value lies between  $0.49$  and  $0.51$ ?

${\rm Min\big[\ Pr(0.49}≤h_0≤0.51)\ \big] \ = \ $

  $\%$

5

How many symbols  $(N_\min)$  would you need to use for this investigation to ensure
that the probability for the event  "The frequency so determined is between  $0.499$  and  $0.501$"  is greater than  $99\%$ ?

$N_\min \ = \ $

$\ \cdot 10^9$


Solution

(1)  Correct are  suggested solutions 3, 4, and 5:

  • The random variables  $\rm (C)$  and  $\rm (D)$  are binary  $(M= 2)$,
  • while the random variable  $\rm (E)$  is trivalent  $(M= 3)$.


(2)  The  proposed solution 1  alone is correct:

  • The random variable  $\rm (A)$  is continuous in value and can take all values between  $\pm 2 \hspace{0.03cm} \rm V$  with equal probability.
  • All other random variables are discrete in value.


(3)  The  proposed solution 2  alone is correct:

  • Only the random variable  $\rm (B)$  has a discrete part at  $0\hspace{0.03cm}\rm V$,  and
  • also has a continuous component  (between  $0\hspace{0.03cm} \rm V$  and  $+2\hspace{0.03cm}\rm V)$.


(4)  According to Bernoulli's law of large numbers:

$$\rm Pr\left(|\it h_{\rm 0} - \it p_{\rm 0}|\ge\it\varepsilon\right)\le\frac{\rm 1}{\rm 4\cdot \it N\cdot\it\varepsilon^{\rm 2}} = {\it p}_{\rm \hspace{0.01cm}Bernouilli}.$$
  • Thus,  the probability that the relative frequency  $h_0$  deviates from the probability  $p_0 = 0.5$  by more than  $0.01$  can be calculated as  $\varepsilon = 0.01$:
$${\it p}_{\rm \hspace{0.01cm}Bernoulli} = \rm\frac{1}{4\cdot 100000\cdot 0.01^2}=\rm 2.5\% \hspace{0.5cm}\Rightarrow \hspace{0.5cm} {\rm Min}\big[({\rm Pr}(0.49 \le h_0 \le 0.51)\big] \hspace{0.15cm}\underline{= 97.5\%}.$$


(5)  With  $p_{\rm Bernoulli} = 1 - 0.99 = 0.01$  and  $\varepsilon = 0.001$  holds again by the law of large numbers:

$${\it p}_{\rm \hspace{0.01cm}Bernoulli}\le\frac{\rm 1}{\rm 4\cdot \it N\cdot\it \varepsilon^{\rm 2}}.$$
  • Solved for  $N$,  one gets:
$$N\ge\frac{\rm 1}{\rm 4\cdot\it p_{\rm \hspace{0.01cm}Bernoulli}\cdot\varepsilon^{\rm 2}}=\rm \frac{1}{4\cdot 0.01\cdot 0.001^{2}}=\rm 0.25\cdot 10^8 \hspace{0.5cm}\Rightarrow \hspace{0.5cm} {\it N}_{\rm min} \hspace{0.15cm}\underline{= 2.5\cdot 10^9}.$$