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Meta-Heuristics hybridizing independent component analysis with genetic algorithms

Górriz, J. M. and Puntonet, Carlos G. and Martin-Clemente, R. and Lang, Elmar (2004) Meta-Heuristics hybridizing independent component analysis with genetic algorithms. In: Proceedings / ICECS 2004: the 11th IEEE International Conference on Electronics, Circuits and Systems; December 13-15, 2004, Tel Aviv, Israel. IEEE Operations Center, Piscataway, NJ, pp. 523-526. ISBN 0-7803-8715-5.

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Abstract

In this work we present a novel method for blindly separating unobservable independent component signals from their linear mixtures, using meta- heuristics such as genetic algorithms (GA) to minimize the nonconvex and nonlinear cost functions. This approach is very useful in many fields such as forecasting indexes in financial stock markets where the search for independent components is the ...

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Export bibliographical data

Item Type:Book Section
Date:2004
Institutions:Biology, Preclinical Medicine > Institut für Biophysik und physikalische Biochemie > Prof. Dr. Elmar Lang
Projects:Graduiertenkolleg Nichtlinearität und Nichtgleichgewicht
Identification Number:
ValueType
10.1109/ICECS.2004.1399733DOI
Subjects:500 Science > 530 Physics
500 Science > 570 Life sciences
Status:Published
Refereed:Yes, this version has been refereed
Created at the University of Regensburg:Yes
Owner: Redakteur Physik
Deposited On:20 Mar 2007
Last Modified:15 Oct 2010 07:57
Item ID:1640
Owner Only: item control page
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