X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/16dcc.git/blobdiff_plain/a57f211cb3b73d523ff516e65f2559b296775c11..79f46c777f6ef3202c2fb25194822518cad3e32c:/stopping.tex?ds=inline diff --git a/stopping.tex b/stopping.tex index 539d653..142da7f 100644 --- a/stopping.tex +++ b/stopping.tex @@ -10,7 +10,7 @@ interpreted as Markov chains. \begin{xpl} Let us consider for instance the graph $\Gamma(f)$ defined -in \textsc{Figure~\ref{fig:iteration:f*}.} and +in Figure~\ref{fig:iteration:f*} and the probability function $p$ defined on the set of edges as follows: $$ p(e) \left\{ @@ -39,13 +39,13 @@ P=\dfrac{1}{6} \left( A specific random walk in this modified hypercube is first -introduced (See section~\ref{sub:stop:formal}). We further +introduced (see Section~\ref{sub:stop:formal}). We further study this random walk in a theoretical way to provide an upper bound of fair sequences -(See section~\ref{sub:stop:bound}). -We finally complete these study with experimental +(see Section~\ref{sub:stop:bound}). +We finally complete this study with experimental results that reduce this bound (Sec.~\ref{sub:stop:exp}). -Notice that for a general references on Markov chains +For a general reference on Markov chains, see~\cite{LevinPeresWilmer2006}, and particularly Chapter~5 on stopping times. @@ -76,7 +76,7 @@ $$t_{\rm mix}(\varepsilon)=\min\{t \mid d(t)\leq \varepsilon\}.$$ %% \textit{i.e.}, is the time until the matrix $X$ of a Markov chain %% is $\epsilon$-close to a stationary distribution. -Intutively speaking, $t_{\rm mix}(\varepsilon)$ is the time/steps required +Intuitively speaking, $t_{\rm mix}(\varepsilon)$ is the time/steps required to be sure to be $\varepsilon$-close to the stationary distribution, wherever the chain starts. @@ -138,7 +138,7 @@ ${\mathsf{N}}$-cube. Let $h$ be a function from $\Bool^{\mathsf{N}}$ into $\llbracket 1, {\mathsf{N}} \rrbracket$. Intuitively speaking $h$ aims at memorizing for each node $X \in \Bool^{\mathsf{N}}$ which edge is removed in the Hamiltonian cycle, -\textit{i.e.} which bit in $\llbracket 1, {\mathsf{N}} \rrbracket$ +\textit{i.e.}, which bit in $\llbracket 1, {\mathsf{N}} \rrbracket$ cannot be switched. @@ -208,7 +208,7 @@ $$ An integer $\ell\in \llbracket 1,{\mathsf{N}} \rrbracket$ is said {\it fair} at time $t$ if there exists $0\leq j t)\leq \frac{E[\tau]}{t}$. With $t_n=32N^2+16N\ln (N+1)$, one obtains: $\P_X(\tau > t_n)\leq \frac{1}{4}$. -Therefore, using the defintion of $t_{\rm mix)}$ and +Therefore, using the definition of $t_{\rm mix}$ and Theorem~\ref{thm-sst}, it follows that $t_{\rm mix}\leq 32N^2+16N\ln (N+1)=O(N^2)$. @@ -377,19 +377,19 @@ are more regular and more binding than this constraint. Moreover, the bound is obtained using the coarse Markov Inequality. For the classical (lazzy) random walk the $\mathsf{N}$-cube, without removing any -Hamiltonian cylce, the mixing time is in $\Theta(N\ln N)$. +Hamiltonian cycle, the mixing time is in $\Theta(N\ln N)$. We conjecture that in our context, the mixing time is also in $\Theta(N\ln N)$. -In this later context, we claim that the upper bound for the stopping time +In this latter context, we claim that the upper bound for the stopping time should be reduced. This fact is studied in the next section. \subsection{Practical Evaluation of Stopping Times}\label{sub:stop:exp} Let be given a function $f: \Bool^{\mathsf{N}} \rightarrow \Bool^{\mathsf{N}}$ and an initial seed $x^0$. -The pseudo code given in algorithm~\ref{algo:stop} returns the smallest +The pseudo code given in Algorithm~\ref{algo:stop} returns the smallest number of iterations such that all elements $\ell\in \llbracket 1,{\mathsf{N}} \rrbracket$ are fair. It allows to deduce an approximation of $E[\ts]$ by calling this code many times with many instances of function and many seeds. @@ -414,19 +414,19 @@ $\textit{fair}\leftarrow\emptyset$\; } \Return{$\textit{nbit}$}\; %\end{scriptsize} -\caption{Pseudo Code of stoping time calculus } +\caption{Pseudo Code of stopping time computation} \label{algo:stop} \end{algorithm} Practically speaking, for each number $\mathsf{N}$, $ 3 \le \mathsf{N} \le 16$, -10 functions have been generated according to method presented in section~\ref{sec:hamilton}. For each of them, the calculus of the approximation of $E[\ts]$ -is executed 10000 times with a random seed. The Figure~\ref{fig:stopping:moy} +10 functions have been generated according to method presented in Section~\ref{sec:hamilton}. For each of them, the calculus of the approximation of $E[\ts]$ +is executed 10000 times with a random seed. Figure~\ref{fig:stopping:moy} summarizes these results. In this one, a circle represents the approximation of $E[\ts]$ for a given $\mathsf{N}$. The line is the graph of the function $x \mapsto 2x\ln(2x+8)$. It can firstly be observed that the approximation is largely -smaller than the upper bound given in theorem~\ref{prop:stop}. +smaller than the upper bound given in Theorem~\ref{prop:stop}. It can be further deduced that the conjecture of the previous section is realistic according the graph of $x \mapsto 2x\ln(2x+8)$.