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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


Abstract

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
Date:2004
Institutions:Biology, Preclinical Medicine > Institut für Biophysik und physikalische Biochemie > Prof. Dr. Elmar Lang
Projects:Graduiertenkolleg Nichtlinearität und Nichtgleichgewicht
Identification Number:
ValueType
10.1016/S0925-2312(03)00378-3DOI
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: Redakteur Physik
Deposited On:20 Mar 2007
Last Modified:04 Oct 2010 08:22
Item ID:1646
Owner Only: item control page
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