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A Canonical Genetic Algorithm for Blind Inversion of Linear Channels

A Canonical Genetic Algorithm for Blind Inversion of Linear Channels
 
Rojas, Fernando ; Solé-Casals, Jordi ; Monte-Moreno, Enric ; Puntonet, Carlos G. ; Prieto, Alberto
2006

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Abstract

It is well known the relationship between source separation and blind deconvolution: If a filtered version of an unknown i.i.d. signal is observed, temporal independence between samples can be used to retrieve the original signal, in the same manner as spatial independence is used for source separation. In this paper we propose ...»»»»
It is well known the relationship between source separation and blind deconvolution: If a filtered version of an unknown i.i.d. signal is observed, temporal independence between samples can be used to retrieve the original signal, in the same manner as spatial independence is used for source separation. In this paper we propose the use of a Genetic Algorithm (GA) to blindly invert linear channels. The use of GA is justified in the case of small number of samples, where other gradient-like methods fails because of poor estimation of statistics.^^^^

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Conference object

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(c) Springer (The original publication is available at www.springerlink.com)
 
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Citation:

Rojas F., Solé Casals Jordi, Monte-Moreno E., Puntonet C. G. and Prieto A. 2006. A canonical genetic algorithm for blind inversion of linear channels. Independent component analysis and blind signal separation, proceedings; LECTURE NOTES IN COMPUTER SCIENCE; 6th international conference on independent component analysis and blind signal separation; MAR 05-08, 2006; Charleston, SC. BERLIN; HEIDELBERGER PLATZ 3, D-14197 BERLIN, GERMANY: SPRINGER-VERLAG BERLIN. 238 p.