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Probability
└── Homework
    └── W5
        └── Q1.tex

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\documentclass[12pt]{article}

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\fancyhead[l]{Li Yifeng}
\fancyhead[c]{Homework \#5}
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\newcommand{\bP}{\mathbb{P}}

\begin{document}

    \section*{Question 1}

    \noindent Consider a binary communication channel, with input $X$ having a Bernoulli distribution with parameter $p = 0.9$. The common error probability is $\epsilon = 0.05$ (i.e., the probability that the received character differs from the input character is $\epsilon$). Let $Y$ denote the output character.

    \bigskip

    \begin{enumerate}[start=1,label={\bfseries Part \arabic*:},leftmargin=0in]
        \bigskip\item Show that $Y$ is a Bernoulli distribution with parameter $q$.

        \subsection*{Solution}

            We know that $X$ has a Bernoulli distribution in sample space $\Omega = \{0,1\}$ (let 0 denotes $not\enspace received$ and 1 denotes $received$) with parameter $p = 0.9$, then easy to see that

            \[
            \begin{aligned}
                \bP(Y=0) &= \bP(X=0)\bP_{X=0}(Y=0) + \bP(X=1)\bP_{X=1}(Y=0)\\
                &= (1-p)(1-\epsilon) + p\epsilon\\
                &= 2p\epsilon - p - \epsilon + 1
            \end{aligned}
            \]

            Similiarly, we have

            \[
            \begin{aligned}
                \bP(Y=1) &= \bP(X=0)\bP_{X=0}(Y=1) + \bP(X=1)\bP_{X=1}(Y=1)\\
                &= (1-p)\epsilon + p(1-\epsilon)\\
                &= -2p\epsilon + p + \epsilon
            \end{aligned}
            \]

            Then we have

            \[
                0 < \bP(Y=0), \bP(Y=1) < 1,\quad\text{and}\quad \bP(Y=0) + \bP(Y=1) = 1
            \]

            Then we can say that $Y$ is a Bernouli distribution in sample space $\Omega = \{0,1\}$ with parameter

            \[
            \begin{aligned}
                q &= \bP(Y = 1)\\
                &= -2p\epsilon + p + \epsilon
            \end{aligned}
            \]

        \subsection*{Answer}

            \[\boxed{\text{See above.}}\]

        \bigskip\item Determine $q$.

        \subsection*{Solution}

            With the explanation and formula above, easy to see that

            \[q = -2p\epsilon + p + \epsilon = 0.86\]

        \subsection*{Answer}

            \[\boxed{q = 0.86}\]

        \bigskip\item Compute the joint probability distribution function of $(X,Y)$.

        \subsection*{Solution}

            Easy to compute the joint distribution function of $(X,Y)$ as

            \[
                f(x,y) =
                    \begin{cases}
                        \begin{aligned}
                            \bP(X=0,Y=0) &= \bP(X=0)\bP_{X = 0}(Y = 0) = &(1-p)1 - \epsilon &= 0.095,&\quad x = 0,\quad y = 0\\
                            \bP(X=0,Y=1) &= \bP(X=0)\bP_{X = 0}(Y = 1) = &(1-p)\epsilon &= 0.005,&\quad x = 0,\quad y = 1\\
                            \bP(X=1,Y=0) &= \bP(X=1)\bP_{X = 1}(Y = 0) = &p\epsilon &= 0.045,&\quad x = 1,\quad y = 0\\
                            \bP(X=1,Y=1) &= \bP(X=1)\bP_{X = 1}(Y = 1) = &p(1 - \epsilon) &= 0.855,&\quad x = 1,\quad y = 1
                        \end{aligned}
                    \end{cases}
            \]

        \subsection*{Answer}

            \[\boxed{f(x,y) =
                \begin{cases}
                    \begin{aligned}
                        0.095,&\quad x = 0,\quad y = 0\\
                        0.005,&\quad x = 0,\quad y = 1\\
                        0.045,&\quad x = 1,\quad y = 0\\
                        0.855,&\quad x = 1,\quad y = 1
                    \end{aligned}
            \end{cases}}\]
    \end{enumerate}

\end{document}