Multichannel blind deconvolution and source separation using the natural gradient

Shu N.Ichi Amari, Scott C. Douglas, Andrzej Cichocki

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

Multichannel deconvolution is an important task for numerous applications in communications, signal processing, and control. In this paper, we extend the efficient natural gradient search method to derive a set of on-line algorithms for combined multichannel blind source separation and time-domain deconvolution of additive, convolved signal mixtures. The algorithms are derived from a maximum differential entropy cost formulation. We prove that the doubly infinite multichannel filtering system possesses the equivariance property such that its asymptotic adaptive behavior depends only on the normalized stochastic distribution of the source signals and not on the mixing characteristics of the unknown channel. Both approximate time- and frequency-domain finite-impulse-response (FIR) implementations of the methods are described. Extensive simulations indicate the ability of the proposed methods to perform efficient simultaneous multichannel deconvolution and source separation.!

Original languageEnglish
Number of pages1
JournalIEEE Transactions on Signal Processing
Volume46
Issue number3
Publication statusPublished - 1998
Externally publishedYes

Fingerprint

Dive into the research topics of 'Multichannel blind deconvolution and source separation using the natural gradient'. Together they form a unique fingerprint.

Cite this