Work

Multichannel blind deconvolution and equalization using the natural gradient

Year: 2002

Type: conference-paper

Abstract: Multichannel deconvolution and equalization is an important task for numerous applications in communications, signal processing, and control. We extend the efficient natural gradient search method of Amari, Cichocki and Yang (see Advances in Neural Information Processing Systems, p.752-63, 1995) to derive a set of on-line algorithms for combined multichannel blind source separation and time-domain deconvolution/equalization of additive, convolved signal mixtures. We prove that the doubly-infinite multichannel equalizer based on the maximum entropy cost function with natural gradient possesses the so-called "equivariance property" such that its asymptotic performance depends on the normalized stochastic distribution of the source signals and not on the characteristics of the unknown channel. Simulations indicate the ability of the algorithm to perform efficient simultaneous multichannel signal deconvolution and source separation.

Source: IEEE International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)

DOI: 10.1109/spawc.1997.630083

Authors: S. Amari, S.C. Douglas, A. Cichocki, H.H. Yang

Institutions: RIKEN, University of Utah

Language: English

Topic: Blind Source Separation Techniques

Subfield: Signal Processing

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W2149014962

FWCI: 38.2

Cites: 12

Cited by: 323

Related to: 10