Difference between revisions of "Aufgaben:Exercise 1.7Z: BARBARA Generator"
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{{quiz-Header|Buchseite=Theory_of_Stochastic_Signals/Markov_Chains}} | {{quiz-Header|Buchseite=Theory_of_Stochastic_Signals/Markov_Chains}} | ||
− | [[File:P_ID454__Sto_Z_1_7.png|right|frame|$BARBARA$ Generator]] | + | [[File:P_ID454__Sto_Z_1_7.png|right|frame|$\rm BARBARA$ Generator]] |
− | Here we consider a ternary random generator with symbols $A$, $B$ and $R$, which can be described by a homogeneous and stationary first order Markov chain. | + | Here we consider a ternary random generator with symbols $A$, $B$ and $R$, which can be described by a homogeneous and stationary first order Markov chain. |
*The transition probabilities can be taken from the sketched Markov diagram. | *The transition probabilities can be taken from the sketched Markov diagram. | ||
*For the first three subtasks, $p = 1/4$ should always hold. | *For the first three subtasks, $p = 1/4$ should always hold. | ||
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Hints: | Hints: | ||
− | *The | + | *The exercise belongs to the chapter [[Theory_of_Stochastic_Signals/Markov_Chains|Markov Chains]]. |
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|type="[]"} | |type="[]"} | ||
- The values of $p > 0$ and $q < 1$ are largely arbitrary. | - The values of $p > 0$ and $q < 1$ are largely arbitrary. | ||
− | + For the transition probabilities, the following must hold: $p + q = 1$. | + | + For the transition probabilities, the following must hold: $p + q = 1$. |
+ All symbols have equal ergodic probabilities. | + All symbols have equal ergodic probabilities. | ||
- It holds here: ${\rm Pr}(A) = 1/2, \; {\rm Pr}(B) = 1/3, \; {\rm Pr}(R) = 1/6$. | - It holds here: ${\rm Pr}(A) = 1/2, \; {\rm Pr}(B) = 1/3, \; {\rm Pr}(R) = 1/6$. | ||
− | {What are the conditional probabilities $p_{\rm A}$, $p_{\rm B}$ and $p_{\rm C}$ that at times between $ν+1$ and $ν+7$ the sequence $BARBARA$ is output, <br>if one is in state | + | {What are the conditional probabilities $p_{\rm A}$, $p_{\rm B}$ and $p_{\rm C}$ that at times between $ν+1$ and $ν+7$ the sequence "$\rm BARBARA$" is output, <br>if one is at time $ν$ in state $A$, $B$ or $R$, respectively? Let $p = 1/4$. |
|type="{}"} | |type="{}"} | ||
$p_{\rm A} \ = \ $ { 0.549 3% } $\ \cdot 10^{-3}$ | $p_{\rm A} \ = \ $ { 0.549 3% } $\ \cdot 10^{-3}$ | ||
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$p_{\rm C} \ = \ $ { 0.183 3% } $\ \cdot 10^{-3}$ | $p_{\rm C} \ = \ $ { 0.183 3% } $\ \cdot 10^{-3}$ | ||
− | {What is the overall probability that the generator outputs the sequence $BARBARA$ | + | {What is the overall probability that the generator outputs the sequence "$\rm BARBARA$"? Let $p = 1/4$ continue to hold. |
|type="{}"} | |type="{}"} | ||
− | ${\rm Pr}(BARBARA)\ = \ $ { 0.244 3% } $\ \cdot 10^{-3}$ | + | ${\rm Pr}(\rm BARBARA)\ = \ $ { 0.244 3% } $\ \cdot 10^{-3}$ |
− | {How should the parameter $p_{\rm opt}$ be chosen to make ${\rm Pr}(BARBARA)$ as large as possible? <br>What is the resulting probability for $BARBARA$? | + | {How should the parameter $p_{\rm opt}$ be chosen to make ${\rm Pr}(\rm BARBARA)$ as large as possible? <br>What is the resulting probability for "$\rm BARBARA$"? |
|type="{}"} | |type="{}"} | ||
$p_{\rm opt} \ = \ $ { 0.8333 3% } | $p_{\rm opt} \ = \ $ { 0.8333 3% } | ||
− | $p = p_{\rm opt}\hspace{-0.1cm}: \hspace{0.3cm}{\rm Pr}(BARBARA)\ = \ $ { 22 3% } $\ \cdot 10^{-3}$ | + | $p = p_{\rm opt}\hspace{-0.1cm}: \hspace{0.3cm}{\rm Pr}(\rm BARBARA)\ = \ $ { 22 3% } $\ \cdot 10^{-3}$ |
</quiz> | </quiz> | ||
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===Musterlösung=== | ===Musterlösung=== | ||
{{ML-Kopf}} | {{ML-Kopf}} | ||
− | '''(1)''' Correct are <u>the second and third suggested solutions</u>: | + | '''(1)''' Correct are <u>the second and third suggested solutions</u>: |
− | *The sum of all outgoing arrows must always be $1$ | + | *The sum of all outgoing arrows must always be $1$. Therefore $q = 1 - p$ holds. |
− | *Because of the symmetry of the Markov diagram, the ergodic probabilities are all equal: | + | *Because of the symmetry of the Markov diagram, the ergodic probabilities are all equal: |
:$${\rm Pr}(A) ={\rm Pr}(B) ={\rm Pr}(R) = 1/3.$$ | :$${\rm Pr}(A) ={\rm Pr}(B) ={\rm Pr}(R) = 1/3.$$ | ||
− | '''(2)''' If one is in the state $B$ at the starting time $\nu= | + | '''(2)''' If one is in the state $B$ at the starting time $\nu=0$, because of ${\rm Pr}(B\hspace{0.05cm}|\hspace{0.05cm}B) = 0$ the state $B$ is not possible at time $\nu=1$. |
− | + | *One fails here already with the initial letter $B$: | |
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− | *One fails here already with the initial letter $B$: | ||
:$$p_{\rm B} \; \underline{ =0}.$$ | :$$p_{\rm B} \; \underline{ =0}.$$ | ||
− | *For the calculation of $p_{\rm A}$ it should be noted: Starting from $A$ one goes in the Markov diagram first to $B$ $($with probability $q)$, then five times clockwise $($each time with probability $p)$ and finally from $R$ to $A$ $($with probability $q)$. Meaning: | + | *For the calculation of $p_{\rm A}$ it should be noted: Starting from $A$ one goes in the Markov diagram first to $B$ $($with probability $q)$, then five times clockwise $($each time with probability $p)$ and finally from $R$ to $A$ $($with probability $q)$. Meaning: |
:$$p_{\rm A} = q^2 \hspace{0.05cm}\cdot \hspace{0.05cm} p^5 = 3^2 / 4^7 \hspace{0.15cm}\underline {\approx 0.549 \hspace{0.05cm}\cdot \hspace{0.05cm} 10^{-3}}.$$ | :$$p_{\rm A} = q^2 \hspace{0.05cm}\cdot \hspace{0.05cm} p^5 = 3^2 / 4^7 \hspace{0.15cm}\underline {\approx 0.549 \hspace{0.05cm}\cdot \hspace{0.05cm} 10^{-3}}.$$ | ||
− | *In a similar way, one obtains: | + | *In a similar way, one obtains: |
:$$p_{\rm R} = q \hspace{0.05cm}\cdot \hspace{0.05cm} p^6 = 3 / 4^7 \hspace{0.15cm}\underline {\approx 0.183 \hspace{0.05cm}\cdot \hspace{0.05cm} 10^{-3}}.$$ | :$$p_{\rm R} = q \hspace{0.05cm}\cdot \hspace{0.05cm} p^6 = 3 / 4^7 \hspace{0.15cm}\underline {\approx 0.183 \hspace{0.05cm}\cdot \hspace{0.05cm} 10^{-3}}.$$ | ||
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'''(3)''' By averaging over the conditional probabilities we obtain: | '''(3)''' By averaging over the conditional probabilities we obtain: | ||
− | :$${\rm Pr}(BARBARA) = p_{\rm A} \hspace{0.05cm}\cdot \hspace{0.05cm} {\rm Pr}(A) \hspace{0.1cm} + \hspace{0.1cm}p_{\rm B} \hspace{0.05cm}\cdot \hspace{0.05cm} {\rm Pr}(B) \hspace{0.1cm} + \hspace{0.1cm}p_{\rm R} \hspace{0.05cm}\cdot \hspace{0.05cm} {\rm Pr}(R).$$ | + | :$${\rm Pr}(\rm BARBARA) = p_{\rm A} \hspace{0.05cm}\cdot \hspace{0.05cm} {\rm Pr}(A) \hspace{0.1cm} + \hspace{0.1cm}p_{\rm B} \hspace{0.05cm}\cdot \hspace{0.05cm} {\rm Pr}(B) \hspace{0.1cm} + \hspace{0.1cm}p_{\rm R} \hspace{0.05cm}\cdot \hspace{0.05cm} {\rm Pr}(R).$$ |
− | This leads to the result: | + | *This leads to the result: |
− | :$${\rm Pr}(BARBARA) = {1}/{3} \cdot \left( q^2 \hspace{0.05cm}\cdot \hspace{0.05cm} p^5 \hspace{0.1cm} +\hspace{0.1cm}0 \hspace{0.1cm} +\hspace{0.1cm}q \hspace{0.05cm}\cdot \hspace{0.05cm} p^6 \right) | + | :$${\rm Pr}(\rm BARBARA) = {1}/{3} \cdot \left( q^2 \hspace{0.05cm}\cdot \hspace{0.05cm} p^5 \hspace{0.1cm} +\hspace{0.1cm}0 \hspace{0.1cm} +\hspace{0.1cm}q \hspace{0.05cm}\cdot \hspace{0.05cm} p^6 \right) |
= \frac{q \hspace{0.05cm}\cdot \hspace{0.05cm} p^5 }{3} \cdot{p+q} | = \frac{q \hspace{0.05cm}\cdot \hspace{0.05cm} p^5 }{3} \cdot{p+q} | ||
= \hspace{-0.15cm} \frac{q \hspace{0.05cm}\cdot \hspace{0.05cm} p^5 }{3} | = \hspace{-0.15cm} \frac{q \hspace{0.05cm}\cdot \hspace{0.05cm} p^5 }{3} | ||
\hspace{0.15cm}\underline { \approx 0.244 \hspace{0.05cm}\cdot \hspace{0.05cm} 10^{-3}}.$$ | \hspace{0.15cm}\underline { \approx 0.244 \hspace{0.05cm}\cdot \hspace{0.05cm} 10^{-3}}.$$ | ||
− | + | '''(4)''' The probability calculated in '''(3)''' is $p^5 \cdot (1-p)/3$, where $q= 1-p$ is considered. | |
− | |||
− | '''(4)''' The probability calculated in '''(3)''' is $p^5 \cdot (1-p)/3$, where $q= 1-p$ is considered. | ||
*By setting the differential to zero, we obtain the governing equation: | *By setting the differential to zero, we obtain the governing equation: | ||
:$$5 \cdot p^4 - 6 \cdot p^5 = 0 \hspace{0.5cm} \Rightarrow \hspace{0.5cm} p_{\rm opt} = 5/6 \hspace{0.15cm}\underline { \approx \rm 0.833}.$$ | :$$5 \cdot p^4 - 6 \cdot p^5 = 0 \hspace{0.5cm} \Rightarrow \hspace{0.5cm} p_{\rm opt} = 5/6 \hspace{0.15cm}\underline { \approx \rm 0.833}.$$ | ||
*This results in a value that is larger than the subtask '''(3)''' by a factor $90$ approximately: | *This results in a value that is larger than the subtask '''(3)''' by a factor $90$ approximately: | ||
− | :$${\rm Pr}(BARBARA) \hspace{0.15cm}\underline { \approx 22 \hspace{0.05cm}\cdot \hspace{0.05cm} 10^{-3}}.$$ | + | :$${\rm Pr}\rm (BARBARA) \hspace{0.15cm}\underline { \approx 22 \hspace{0.05cm}\cdot \hspace{0.05cm} 10^{-3}}.$$ |
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{{ML-Fuß}} | {{ML-Fuß}} |
Latest revision as of 17:29, 2 December 2021
Here we consider a ternary random generator with symbols $A$, $B$ and $R$, which can be described by a homogeneous and stationary first order Markov chain.
- The transition probabilities can be taken from the sketched Markov diagram.
- For the first three subtasks, $p = 1/4$ should always hold.
Hints:
- The exercise belongs to the chapter Markov Chains.
Questions
Musterlösung
(1) Correct are the second and third suggested solutions:
- The sum of all outgoing arrows must always be $1$. Therefore $q = 1 - p$ holds.
- Because of the symmetry of the Markov diagram, the ergodic probabilities are all equal:
- $${\rm Pr}(A) ={\rm Pr}(B) ={\rm Pr}(R) = 1/3.$$
(2) If one is in the state $B$ at the starting time $\nu=0$, because of ${\rm Pr}(B\hspace{0.05cm}|\hspace{0.05cm}B) = 0$ the state $B$ is not possible at time $\nu=1$.
- One fails here already with the initial letter $B$:
- $$p_{\rm B} \; \underline{ =0}.$$
- For the calculation of $p_{\rm A}$ it should be noted: Starting from $A$ one goes in the Markov diagram first to $B$ $($with probability $q)$, then five times clockwise $($each time with probability $p)$ and finally from $R$ to $A$ $($with probability $q)$. Meaning:
- $$p_{\rm A} = q^2 \hspace{0.05cm}\cdot \hspace{0.05cm} p^5 = 3^2 / 4^7 \hspace{0.15cm}\underline {\approx 0.549 \hspace{0.05cm}\cdot \hspace{0.05cm} 10^{-3}}.$$
- In a similar way, one obtains:
- $$p_{\rm R} = q \hspace{0.05cm}\cdot \hspace{0.05cm} p^6 = 3 / 4^7 \hspace{0.15cm}\underline {\approx 0.183 \hspace{0.05cm}\cdot \hspace{0.05cm} 10^{-3}}.$$
(3) By averaging over the conditional probabilities we obtain:
- $${\rm Pr}(\rm BARBARA) = p_{\rm A} \hspace{0.05cm}\cdot \hspace{0.05cm} {\rm Pr}(A) \hspace{0.1cm} + \hspace{0.1cm}p_{\rm B} \hspace{0.05cm}\cdot \hspace{0.05cm} {\rm Pr}(B) \hspace{0.1cm} + \hspace{0.1cm}p_{\rm R} \hspace{0.05cm}\cdot \hspace{0.05cm} {\rm Pr}(R).$$
- This leads to the result:
- $${\rm Pr}(\rm BARBARA) = {1}/{3} \cdot \left( q^2 \hspace{0.05cm}\cdot \hspace{0.05cm} p^5 \hspace{0.1cm} +\hspace{0.1cm}0 \hspace{0.1cm} +\hspace{0.1cm}q \hspace{0.05cm}\cdot \hspace{0.05cm} p^6 \right) = \frac{q \hspace{0.05cm}\cdot \hspace{0.05cm} p^5 }{3} \cdot{p+q} = \hspace{-0.15cm} \frac{q \hspace{0.05cm}\cdot \hspace{0.05cm} p^5 }{3} \hspace{0.15cm}\underline { \approx 0.244 \hspace{0.05cm}\cdot \hspace{0.05cm} 10^{-3}}.$$
(4) The probability calculated in (3) is $p^5 \cdot (1-p)/3$, where $q= 1-p$ is considered.
- By setting the differential to zero, we obtain the governing equation:
- $$5 \cdot p^4 - 6 \cdot p^5 = 0 \hspace{0.5cm} \Rightarrow \hspace{0.5cm} p_{\rm opt} = 5/6 \hspace{0.15cm}\underline { \approx \rm 0.833}.$$
- This results in a value that is larger than the subtask (3) by a factor $90$ approximately:
- $${\rm Pr}\rm (BARBARA) \hspace{0.15cm}\underline { \approx 22 \hspace{0.05cm}\cdot \hspace{0.05cm} 10^{-3}}.$$