An Independent Component Analysis Evolution Based Method for Nonlinear Speech Processing

Authors:
F. Rojas;C. G. Puntonet;I. Rojas;J. Ortega
Affiliations:
Dpto. Arquitectura. y Tecnología de Computadores, University of Granada, Spain;Dpto. Arquitectura. y Tecnología de Computadores, University of Granada, Spain;Dpto. Arquitectura. y Tecnología de Computadores, University of Granada, Spain;Dpto. Arquitectura. y Tecnología de Computadores, University of Granada, Spain
Venue:
IWANN '03 Proceedings of the 7th International Work-Conference on Artificial and Natural Neural Networks: Part II: Artificial Neural Nets Problem Solving Methods
Year:
2009

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Abstract

This paper proposes a novel Independent Component Analysis algorithm based on the use of genetic algorithms intended for its application to the field of non-linear speech processing. Independent Component Analysis (ICA) is a method for finding underlying factors from multidimensional statistical data, so it can be efficiently applied to suppress interferences and demodulate information in Multilnput-MuliOutput (MIMO) systems.