A genetic algorithm for solving BSS-ICA

Abstract

In this paper we proposed a genetic algorithm to minimize a nonconvex and nonlinear cost function based on statistical estimators for solving blind source separation-independent component analysis problem. In this way a novel method for blindly separating unobservable independent component signals from their linear and non linear (using mapping functions) mixtures is devised. The GA presented in this work is able to extract independent components with faster rate than the previous independent component analysis algorithms based on Higher Order Statistics (HOS) as input space dimension increases showing significant accuracy and robustness. © 2006 Springer.