A mutually referenced blind multiuser separation of convolutive mixture algorithm
type: Item
instance of: scholarly article
title: A mutually referenced blind multiuser separation of convolutive mixture algorithm
zbMATH Open document ID: 0985.94014
DOI: 10.1016/S0165-1684(00)00279-6
published in: Signal Processing
publication date: 2002-03-03T00:00:00Z
review text: We present a new subspace adaptive algorithm for the blind separation 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 approach 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 to minimize the subspace criterion. The experimental results show that the convergence of our algorithm is improved due to the use of the conjugate gradient method.
Mathematics Subject Classification ID: 94A12
Mathematics Subject Classification ID: 65K05
zbMATH DE Number: 1715693
zbMATH Keywords: subspace approach
zbMATH Keywords: second- and higher-order statistics
zbMATH Keywords: Sylvester matrix
zbMATH Keywords: blind separation
zbMATH Keywords: convolutive mixture
zbMATH Keywords: conjugate gradient
MaRDI profile type: Publication
full work available at URL: s0165-1684(00)00279-6
OpenAlex ID: W1994927648
Wikidata QID: Q127452153
author: A. Mansour
description: scientific article; zbMATH DE number 1715693