This paper presents a tutorial review of the problem of Blind Source Separation (BSS) and the properties of the classic adaptive algorithms when either the scoree function or a general (non-score) nonlinearity is employed in the algorithm. In new ndings it is shown that the separating solution for both sub-and super-Gausss ian signals can be stabilized by an algorithm employing any given nonlin...

In this paper we present a semipara metric approach to blind separation of nonlinear dy namical systems with linear output equations First we formulate blind deconvolution in a framework of semiparametric model and derive a family of estimat ing functions for the blind separation problem by using a nonholonomic reparametrization The natural gradi ent learning algorithm is derived in the semipar...

A parametric procedure for the blind inversion of nonlinear channels is proposed, based on a recent method of blind source separation in nonlinear mixtures. Experiments show that the proposed algorithms perform efficiently, even in the presence of hard distortion. The method, based on the minimisation of the output mutual information, needs the knowledge of logderivative of input distribution (...

Ground-based solar image restoration is a computationally expensive procedure that involves nonlinear optimization techniques. The presence of atmospheric turbulence produces perturbations in individual images make it necessary to apply blind deconvolution These techniques rely on the observation many short exposure frames are used simultaneously infer instantaneous state atmosphere and unpertu...