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A neural implementation of the JADE algorithm using higher-order neurons

Ziegaus, Ch. and Lang, Elmar (2004) A neural implementation of the JADE algorithm using higher-order neurons. Neurocomputing 56, pp. 79-100.

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Other URL: http://www.elsevier.com/wps/find/journaldescription.cws_home/505628/description#description


A neural implementation of the JADE algorithm, called nJADE, is developed which adaptively determines the mixing matrices to be jointly diagonalized with the JADE algorithm. This alleviates the problem of algebraically determining these mixing matrices which becomes a very tedious if not impossible undertaking with high dimensional data. The new learning rule uses higher-order neurons ...


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Item type:Article
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:1646
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