This work has first shown that iterations of
$G_f$ are chaotic if and only if its iteration graph $\Gamma_{\mathcal{P}}(f)$
is strongly connected where $\mathcal{P}$ is $\{p_1, \ldots, p_{\mathds{p}}\}$.
-Any PRNG, which iterates $G_f$ as above
-satisfies in some cases the property of chaos.
+It can be deduced that in such a situation a PRNG, which iterates $G_f$
+satisfies the property of chaos and can be used in simulating chaos
+phenomenon.
We then have shown that a previously presented approach can be directly
applied here to generate function $f$ with strongly connected
$\Gamma_{\mathcal{P}}(f)$.
The iterated map inside the generator is built by first removing from a
-$\mathsf{N}$-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.
+Thanks to this solution, many chaotic functions can be generated.
+
+
+
+We furthermore have exhibited a upper bound on the number of iterations
+that is sufficient to obtain a uniform distribution of the output.
+Such a 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.
+
Finally, experiments through the NIST battery have shown that
the statistical properties are almost established for
-$\mathsf{N} = 4, 5, 6, 7, 8$.
+ $\mathsf{N} = 4, 5, 6, 7, 8$ and should be observed for any
+positive integer $\mathsf{N}$.
In future work, we intend to understand the link between
statistical tests and the properties of chaos for
By doing so, relations between desired statistically unbiased behaviors and
topological properties will be understood, leading to better choices
in iteration functions.
+
Conditions allowing the reduction of the stopping-time will be
investigated too, while other modifications of the hypercube will
be regarded in order to enlarge the set of known chaotic
and random iterations.
+
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