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A Histogram-Based Overcomplete ICA Algorithm

Theis, Fabian J., Puntonet, Carlos G. and Lang, Elmar (2003) A Histogram-Based Overcomplete ICA Algorithm. In: Amari, S., (ed.) Proceedings / Fourth International Symposium on Independent Component Analysis and Blind Signal Separation, April 1 - 4, 2003, Nara, Japan. Tokyo, pp. 1071-1076. ISBN 4-9901531-1-1.

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Other URL: http://homepages.uni-regensburg.de/~thf11669/publications/theis03fastgeoovercomplete_ICA03.pdf


Overcomplete blind source separation (BSS) tries to recover more sources from less sensor signals. We present a new approach based on an estimated histogram of the sensor data; we search for the points fulfilling the overcomplete Geometric Convergence Condition, which has been shown to be a limit condition of overcomplete geometric BSS. The paper concludes with an example and a comparison of various overcomplete BSS algorithms.

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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
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:1563
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