We use natural gradient (NG) learning neural networks (NNs) for modeling and identifying
nonlinear systems with memory. The nonlinear system is comprised of a discrete-time linear …

Blind identification of second order Hammerstein series is considered in this paper. The
output cumulants up to order 5 are used to determine the Volterra kernels and the system …

This paper is concerned with the blind identification of a class of bilinear systems excited by
non-Gaussian higher order white noise. The matrix of coefficients of mixed input-output …

L'analyse en composantes indépendantes (ACI) est une approche très générale qui a été
développée pour résoudre le problème de séparation aveugle de sources (SAS) …

The paper proposes a sequential Monte Carlo simulation method for equalizing a satellite
communication channel. The main difficulties encountered are the nonlinear distortions due …

This chapter applies the natural gradient (NG) descent for adaptive identification of
nonlinear channels with memory. The nonlinear channel is comprised of a discrete-time …

This subproject considered ICA and BSS problems for nonlinear data models. In that case,
ICA is characterized by severe indeterminacies, which makes the BSS problem ill-posed …