-$\mathsf{N}$-cube an Hamiltonian path and next
-adding a self loop to each vertex.
-The PRNG can thus be seen as a random walks of length in $\mathsf{P}$
-into $\mathsf{N}$ this new cube.
-We furthermore have exhibit a bound on the number of iterations
-that are sufficient to obtain a uniform distribution of the output.
+$\mathsf{N}$-cube a balanced Hamiltonian cycle and next
+by adding a self loop to each vertex.
+The PRNG can thus be seen as a random walk of length in $\mathcal{P}$
+into this new $\mathsf{N}$-cube.
+We have exhibit an efficient method to compute such a balanced Hamiltonian
+cycle. This method is an algebraic solution of an undeterministic
+approach~\cite{ZanSup04} and has a low complexity.
+According to the authors knowledge, this is the first time a full
+automatic method to provide chaotic PRNGs is given.
+Practically speaking, this approach preserves the security properties of
+the embedded PRNG, even if it remains quite cost expensive.
+
+
+We furthermore have exhibited an upper bound on the number of iterations
+that is sufficient to obtain an uniform distribution of the output.
+Such an upper bound is quadratic on the number of bits to output.
+Experiments have however shown that such a bound is in
+$\mathsf{N}.\log(\mathsf{N})$ in practice.