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Linear Geometric ICA: Fundamentals and Algorithms

Theis, Fabian J. and Jung, Andreas and Puntonet, Carlos G. and Lang, Elmar W. (2003) Linear Geometric ICA: Fundamentals and Algorithms. Neural Computation 15, pp. 419-439.

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Other URL: http://neco.mitpress.org/cgi/content/abstract/15/2/419?maxtoshow=&HITS=10&hits=10&RESULTFORMAT=&searchid=1105816667459_105&stored_search=&FIRSTINDEX=0&sortspec=relevance&volume=15&firstpage=419&journalcode=neco


Abstract

Geometric algorithms for linear independent component analysis (ICA) have recently received some attention due to their pictorial description and their relative ease of implementation. The geometric approach to ICA was proposed first by Puntonet and Prieto (1995). We will reconsider geometric ICA in a theoretic framework showing that fixed points of geometric ICA fulfill a geometric ...

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Item Type:Article
Date:2003
Institutions:Biology, Preclinical Medicine > Institut für Biophysik und physikalische Biochemie > Prof. Dr. Elmar Lang
Physics > Institute of Theroretical Physics > Chair Professor Richter > Group Klaus Richter
Projects:Graduiertenkolleg Nichtlinearität und Nichtgleichgewicht
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: Timo Hartmann
Deposited On:20 Mar 2007
Last Modified:13 Mar 2014 09:57
Item ID:1516
Owner Only: item control page
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