A mutually referenced blind multiuser separation of convolutive mixture algorithm

In this paper, we present a new subspace adaptive algorithm for the blind s eparation problem of a convolutive mixture. The major advantage of such an algorithm is that almost all the unknown parameters of the inverse channel can be estimated using only second-order statistics. In fact, a subspace ap proach was used to transform the convolutive mixture into an instantaneous mixture using a criterion of second-order statistics. It is known that the convergence of subspace algorithms is in general, very slow. To improve the convergence speed of our algorithm, a conjugate gradient method was used t o minimize the subspace criterion. The experimental results show that the c onvergence of our algorithm is improved due to the use of the conjugate gra dient method, (C) 2001 Elsevier Science B.V. All rights reserved.