We define the Markov matrix $P_h$ for each line $X$ and
each column $Y$ as follows:
-$$\left\{
+\begin{equation}
+\left\{
\begin{array}{ll}
P_h(X,X)=\frac{1}{2}+\frac{1}{2{\mathsf{N}}} & \\
P_h(X,Y)=0 & \textrm{if $(X,Y)\notin E_h$}\\
P_h(X,Y)=\frac{1}{2{\mathsf{N}}} & \textrm{if $X\neq Y$ and $(X,Y) \in E_h$}
\end{array}
\right.
-$$
+\label{eq:Markov:rairo}
+\end{equation}
We denote by $\ov{h} : \Bool^{\mathsf{N}} \rightarrow \Bool^{\mathsf{N}}$ the function
such that for any $X \in \Bool^{\mathsf{N}} $,
