\documentclass{ita}
\usepackage{graphicx}
+\usepackage{caption}
+\usepackage{subcaption}
+
\usepackage{dsfont}
\usepackage{stmaryrd}
-\usepackage[font=footnotesize]{subfig}
+%\usepackage[font=footnotesize]{subfig}
\usepackage{ifthen}
\usepackage{color}
\usepackage{algorithm2e}
\usepackage{epstopdf}
+%\usepackage{ntheorem}
-
-\usepackage[latin1]{inputenc}
+\usepackage[utf8]{inputenc}
\usepackage[T1]{fontenc}
\usepackage[english]{babel}
\usepackage{amsmath,amssymb,latexsym,eufrak,euscript}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-% Définitions personnelles
+% Définitions personnelles
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\definecolor{bleuclair}{rgb}{0.75,0.75,1.0}
\def \ts {\tau_{\rm stop}}
-% \theoremstyle{plain}
-% \theoremheaderfont{\normalfont\bfseries\sc}
-% \theorembodyfont{\slshape}
-% \theoremsymbol{\ensuremath{\diamondsuit}}
-% \theoremprework{\bigskip}
-% \theoremseparator{.}
-\newtheorem{Def}{\underline{Definition}}
-\newtheorem{Lemma}{\underline{Lemma}}
-\newtheorem{Theo}{\underline{Theorem}}
-% \theoremheaderfont{\sc}
-% \theorembodyfont{\upshape}
-% \theoremstyle{nonumberplain}
-% \theoremseparator{}
-% \theoremsymbol{\rule{1ex}{1ex}}
-\newtheorem{Proof}{Proof}
+\newtheorem{Def}{Definition}
+%\newtheorem{Lemma}{\underline{Lemma}}
+\newtheorem{Theo}{Theorem}
+\newtheorem{Corollary}{Corollary}
+\newtheorem{Lemma}{Lemma}
\newtheorem{proposition}{Proposition}
-\newtheorem{xpl}{Running Example}
+\newtheorem*{xpl}{Running Example}
\newcommand{\vectornorm}[1]{\ensuremath{\left|\left|#1\right|\right|_2}}
%\newcommand{\ie}{\textit{i.e.}}
-\title{XXX}
+\title{Random Walk in a N-cube Without Hamiltonian Cycle
+ to Chaotic Pseudorandom Number Generation: Theoretical and Practical
+ Considerations}
\begin{document}
-\author{Jean-François Couchot, Christophe Guyeux, Pierre-Cyrile Heam}
-\address{Institut FEMTO-ST, Université de Franche-Comté, Belfort, France}
+\author{Jean-François Couchot, Christophe Guyeux, Pierre-Cyrile Heam}
+\address{Institut FEMTO-ST, Université de Franche-Comté, Belfort, France}
-%\author{Sylvain Contassot-Vivier}
-%\address{Loria - UMR 7503, Université de Lorraine, Nancy, France}
-\date{...}
\begin{abstract}
-This paper extends the results presented in~\cite{bcgr11ip}
-and~\cite{chgw14oip} by using the \emph{chaotic} updating mode, in the sense
-of F. Robert~\cite{Robert}. In this mode, several components of the system
-may be updated at each iteration. At the theoretical level, we show that
- the properties of chaos and uniformity of the obtained PRNG are preserved.
- At the practical level, we show that the algorithm that builds strongly
- connected iteration graphs, with doubly stochastic Markov matrix, has a
- reduced mixing time.
+This paper is dedicated to the design of chaotic random generators
+and extends previous works proposed by some of the authors.
+We propose a theoretical framework proving both the chaotic properties and
+that the limit distribution is uniform.
+A theoretical bound on the stationary time is given and
+practical experiments show that the generators successfully passe
+the classical statsitcal tests.
\end{abstract}
+\maketitle
+
\section{Introduction}
-%\input{intro}
+\input{intro}
\section{\uppercase{Preliminaries}}\label{sec:preliminaries}
\input{preliminaries}
-\section{Proof Of Chaos}
-\JFC{Enlever les refs aux PRNGs, harmoniser l'exemple}
+\section{Proof Of Chaos}\label{sec:proofOfChaos}
\input{chaos}
-\section{Generating....}
-\JFC{Reprendre Mons en synthétisant... conclusion: n-cube moins hamitonien.
-question efficacité d'un tel algo}
-%\input{chaos}
+\section{Functions with Strongly Connected $\Gamma_{\{b\}}(f)$}\label{sec:SCCfunc}
+\input{generating}
-\section{Random walk on the modified Hypercube}
+\section{Random walk on the modified Hypercube}\label{sec:hypercube}
\input{stopping}
% Donner la borne du stopping time quand on marche dedans (nouveau).
-% Énoncer le problème de la taille de cette borne
+% Énoncer le problème de la taille de cette borne
% (elle est certes finie, mais grande).
%\section{Quality study of the strategy}
-%6) Se pose alors la question de comment générer une stratégie de "bonne qualité". Par exemple, combien de générateurs aléatoires embarquer ? (nouveau)
+%6) Se pose alors la question de comment générer une stratégie de "bonne qualité". Par exemple, combien de générateurs aléatoires embarquer ? (nouveau)
-\section{Application to Pseudorandom Number Generation}
+\section{Application to Pseudorandom Number Generation}\label{sec:prng}
\input{prng}
-\JFC{ajouter ici les expérimentations}
+\JFC{ajouter ici les expérimentations}
\section{Conclusion}
