Difference between revisions of "Aufgaben:Exercise 1.1Z: Sum of Two Ternary Signals"
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{{quiz-Header|Buchseite=Stochastische Signaltheorie/Einige grundlegende Definitionen}} | {{quiz-Header|Buchseite=Stochastische Signaltheorie/Einige grundlegende Definitionen}} | ||
− | [[File:P_ID146__Sto_Z1_1.png|right|framed| | + | [[File:P_ID146__Sto_Z1_1.png|right|framed|Sum $S$ of two <br>ternary signals $X$ and $Y$]] |
− | + | Let two three-stage message sources $X$ and $Y$, be given, whose output signals can only assume the values $-1$, $0$ and $+1$ respectively. The signal sources are statistically independent of each other. | |
− | * | + | *A simple circuit now forms the sum signal $S = X + Y$. |
− | * | + | *At the signal source $X$ the values $-1$, $0$ and $+1$ occur with equal probability. |
− | * | + | *For source $Y$ , the signal value $0$ is twice as likely as the other two values $-1$ and $+1$, respectively. |
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− | + | Hints: | |
− | + | *The exercise belongs to the chapter [[Theory_of_Stochastic_Signals/Einige_grundlegende_Definitionen | Some basic definitions of probability theory]]. | |
− | * | ||
− | * | + | *Solve the subtasks '''(3)''' and '''(4)''' according to the classical definition. |
− | * | + | *Nevertheless, consider the different occurrence frequencies of the signal $Y$. |
− | * | + | *The topic of this section is illustrated with examples in the (German language) learning video [[Klassische_Definition_der_Wahrscheinlickeit_(Lernvideo)|Klassische Definition der Wahrscheinlichkeit]] $\Rightarrow$ "Classical definition of probability". |
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− | === | + | ===Questions=== |
<quiz display=simple> | <quiz display=simple> | ||
− | { | + | {What are the probabilities of occurrence of the signal values of $Y$? What is the probability that $Y = 0$ ? |
|type="{}"} | |type="{}"} | ||
${\rm Pr}(Y=0) \ = \ $ { 0.5 3% } | ${\rm Pr}(Y=0) \ = \ $ { 0.5 3% } | ||
− | { | + | {How many different signal values $(I)$ can the sum signal $S$ assume? Which are these? |
|type="{}"} | |type="{}"} | ||
$ I \ = \ $ { 5 3% } | $ I \ = \ $ { 5 3% } | ||
− | { | + | {What are the probabilities of the values determined in subtask '''(2)''' ? How probable is the maximum value $S_{\rm max}$? |
|type="{}"} | |type="{}"} | ||
$ {\rm Pr}(S = S_{\rm max} ) \ = \ $ { 0.0833 3% } | $ {\rm Pr}(S = S_{\rm max} ) \ = \ $ { 0.0833 3% } | ||
− | { | + | {How do the probabilities change, if now instead of the sum the difference $D = X - Y$ is considered? Give reasons for your answer. |
|type="[]"} | |type="[]"} | ||
− | + | + | + The probabilities remain the same. |
− | - | + | - The probabilities change. How do they change? |
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</quiz> | </quiz> | ||
− | === | + | ===Solution=== |
{{ML-Kopf}} | {{ML-Kopf}} | ||
− | '''(1)''' | + | '''(1)''' Since the probabilities of $ \pm 1$ are the same and ${\rm Pr}(Y = 0) = 2 \cdot {\rm Pr}(Y = 1)$ holds, we get: |
:$${\rm Pr}(Y = 1) + {\rm Pr}(Y = 0) + {\rm Pr}(Y = -1) = 1/2 \cdot {\rm Pr}(Y = 0) + {\rm Pr}(Y = 0) + 1/2\cdot {\rm Pr}(Y = 0) = 1\hspace{0.3cm} \Rightarrow \hspace{0.3cm}{\rm Pr}(Y = 0)\;\underline { = 0.5}. $$ | :$${\rm Pr}(Y = 1) + {\rm Pr}(Y = 0) + {\rm Pr}(Y = -1) = 1/2 \cdot {\rm Pr}(Y = 0) + {\rm Pr}(Y = 0) + 1/2\cdot {\rm Pr}(Y = 0) = 1\hspace{0.3cm} \Rightarrow \hspace{0.3cm}{\rm Pr}(Y = 0)\;\underline { = 0.5}. $$ | ||
− | '''(2)''' $S$ | + | '''(2)''' $S$ can take a total of $\underline {I =5}$ values, namely $0$, $\pm 1$ and $\pm 2$. |
− | [[File:EN_Sto_Z1_1_c.png|right|frame|400px| | + | [[File:EN_Sto_Z1_1_c.png|right|frame|400px|Sum and difference of ternary random variables]] |
− | '''(3)''' | + | '''(3)''' Since $Y$ is not equally distributed, one cannot (actually) apply the "Classical Definition of Probability" here. |
− | * | + | *However, if we divide $Y$ into four ranges according to the graph, assigning two of the ranges to the event $Y = 0$ , we can still proceed according to the classical definition. |
− | * | + | *One then obtains: |
:$${\rm Pr}(S = 0) = {4}/{12} = {1}/{3},$$ | :$${\rm Pr}(S = 0) = {4}/{12} = {1}/{3},$$ | ||
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− | '''(4)''' | + | '''(4)''' It is also evident from the graph that the difference signal $D$ and the sum signal $S$ take the same values with equal probabilities. |
− | * | + | *This was to be expected, since ${\rm Pr}(Y = +1) ={\rm Pr}(Y = -1)$ is given ⇒ <u>Proposed solution 1</u>. |
{{ML-Fuß}} | {{ML-Fuß}} | ||
Revision as of 11:37, 15 November 2021
Let two three-stage message sources $X$ and $Y$, be given, whose output signals can only assume the values $-1$, $0$ and $+1$ respectively. The signal sources are statistically independent of each other.
- A simple circuit now forms the sum signal $S = X + Y$.
- At the signal source $X$ the values $-1$, $0$ and $+1$ occur with equal probability.
- For source $Y$ , the signal value $0$ is twice as likely as the other two values $-1$ and $+1$, respectively.
Hints:
- The exercise belongs to the chapter Some basic definitions of probability theory.
- Solve the subtasks (3) and (4) according to the classical definition.
- Nevertheless, consider the different occurrence frequencies of the signal $Y$.
- The topic of this section is illustrated with examples in the (German language) learning video Klassische Definition der Wahrscheinlichkeit $\Rightarrow$ "Classical definition of probability".
Questions
Solution
(1) Since the probabilities of $ \pm 1$ are the same and ${\rm Pr}(Y = 0) = 2 \cdot {\rm Pr}(Y = 1)$ holds, we get:
- $${\rm Pr}(Y = 1) + {\rm Pr}(Y = 0) + {\rm Pr}(Y = -1) = 1/2 \cdot {\rm Pr}(Y = 0) + {\rm Pr}(Y = 0) + 1/2\cdot {\rm Pr}(Y = 0) = 1\hspace{0.3cm} \Rightarrow \hspace{0.3cm}{\rm Pr}(Y = 0)\;\underline { = 0.5}. $$
(2) $S$ can take a total of $\underline {I =5}$ values, namely $0$, $\pm 1$ and $\pm 2$.
(3) Since $Y$ is not equally distributed, one cannot (actually) apply the "Classical Definition of Probability" here.
- However, if we divide $Y$ into four ranges according to the graph, assigning two of the ranges to the event $Y = 0$ , we can still proceed according to the classical definition.
- One then obtains:
- $${\rm Pr}(S = 0) = {4}/{12} = {1}/{3},$$
- $${\rm Pr}(S = +1) = {\rm Pr}(S = -1) ={3}/{12} = {1}/{4},$$
- $${\rm Pr}(S = +2) = {\rm Pr}(S = -2) ={1}/{12}$$
- $$\Rightarrow \hspace{0.3cm}{\rm Pr}(S = S_{\rm max}) = {\rm Pr}(S = +2) =1/12 \;\underline {= 0.0833}.$$
(4) It is also evident from the graph that the difference signal $D$ and the sum signal $S$ take the same values with equal probabilities.
- This was to be expected, since ${\rm Pr}(Y = +1) ={\rm Pr}(Y = -1)$ is given ⇒ Proposed solution 1.