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Meta-Heuristics hybridizing independent component analysis with genetic algorithms

Górriz, J. M., Puntonet, Carlos G., 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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Other URL: http://www.ee.bgu.ac.il/~icecs04/


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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Item type:Book section
Institutions:Biology, Preclinical Medicine > Institut für Biophysik und physikalische Biochemie > Prof. Dr. Elmar Lang
Projects:Graduiertenkolleg Nichtlinearität und Nichtgleichgewicht
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Dewey Decimal Classification:500 Science > 530 Physics
500 Science > 570 Life sciences
Refereed:Yes, this version has been refereed
Created at the University of Regensburg:Yes
Item ID:1640
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