Maximization of statistical moments for blind separation of sources revisited

Authors:
Susana Hornillo-Mellado;Rubén Martín-Clemente;Carlos G. Puntonet;José I. Acha;Juan Manuel Górriz-Sáez
Affiliations:
Dpto. de Teoría de la Señal y Comunicaciones, Escuela Superior de Ingenieros, Universidad de Sevilla, Avda. de los Descubrimientos s/n., 41092-Sevilla, Spain;Dpto. de Teoría de la Señal y Comunicaciones, Escuela Superior de Ingenieros, Universidad de Sevilla, Avda. de los Descubrimientos s/n., 41092-Sevilla, Spain;Dpto. de Arquitectura y Tecnología de Computadores, Universidad de Granada, C/Periodista Daniel Saucedo s/n, 18071-Granada, Spain;Dpto. de Teoría de la Señal y Comunicaciones, Escuela Superior de Ingenieros, Universidad de Sevilla, Avda. de los Descubrimientos s/n., 41092-Sevilla, Spain;Dpto. de Teoría de la Señal, Telemática y Comunicaciones, Universidad de Granada, C/Periodista Daniel Saucedo s/n, 18071-Granada, Spain
Venue:
Neurocomputing
Year:
2006

Citing 9
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Abstract

In this paper we revisit a classic HOS-based BSS criterion, namely the maximization of the higher-order moments of the estimated sources. The main contributions of this paper are: (i) a thorough study of the solutions given by popular HOS-based BSS criteria (including spurious solutions) and (ii) a method for estimating the source signals based on the eigendecomposition of certain adjustable HOS-matrices. Results are illustrated by computer simulations.