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Linear Geometric ICA: Fundamentals and Algorithms

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

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Date of publication of this fulltext: 05 Aug 2009 13:30

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


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
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
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:1516
Owner only: item control page


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