Neuronal networks are characterized by highly heterogeneous connectivity, and this
disorder was recently related experimentally to qualitative properties of the network. The …

This paper is a review dealing with the study of large size random recurrent neural networks.
The connection weights are varying according to a probability law and it is possible to …

In a series of two papers, we investigate the large deviations and asymptotic behavior of
stochastic models of brain neural networks with random interaction coefficients. In this first …

Taking a global analogy with the structure of perceptual biological systems, we present a
system composed of two layers of real-valued sigmoidal neurons. The primary layer …

In der vorliegenden Arbeit werden rekurrente neuronale Netze im Hinblick auf ihre Eignung
zur Bewegungssteuerung autonomer Roboter untersucht. Nacheinander werden …

L'intelligence en essaim constitue désormais un domaine à part entière de l'intelligence
artificielle distribuée. Les problématiques qu'elle soulève touchent cependant à de …

This paper presents the guidelines of an ongoing project of the" Movement Dynamics" team
in the “Movement and perception” Lab, UMR6152, Marseille. We address the question of …

This paper is a presentation of neuronal control systems in the terms of the dynamical
systems theory, where (1) the controller and its surrounding environment are seen as two co …

Recurrent spiking neural networks can provide biologically inspired model of robot
controller. We study here the dynamics of large size randomly connected networks thanks …

We propose an approach to the analysis of the influence of the topology of a neural network
on its synchronizability in the sense of equal output activity rates given by a particular neural …