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Neural implementation of the JADE-algorithm

Ziegaus, Christian and Lang, Elmar (1999) Neural implementation of the JADE-algorithm. In: Mira, José, (ed.) Engineering Applications of Bio-Inspired Artificial Neural Networks. IWANN’99, Alicante, Spain, June 2–4, 1999. Proceedings, Volume 2. Lecture notes in computer science, 1607. Springer, Berlin, pp. 487-496. ISBN 3-540-66068-2 (print und e-book).

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The Joint Approaximative Diagonalization of Eigenmatrices (JADE)-algorithm [6] is an algebraic approach for Indenpendent Component Analysis (ICA), a recent data analysis technique. The basic assumption of ICA is a linear superposition model where unknown source signals are mixed together by a mixing matrix. The aims is to recover the sources respectively the mixing matrix based upon the mixtures ...


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Item type:Book section
Institutions:Biology, Preclinical Medicine > Institut für Biophysik und physikalische Biochemie > Prof. Dr. Elmar Lang
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Dewey Decimal Classification:500 Science > 570 Life sciences
Created at the University of Regensburg:Unknown
Item ID:16850
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