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Adaptive differential decorrelation: A natural gradient algorithm SCIE SCOPUS

Title
Adaptive differential decorrelation: A natural gradient algorithm
Authors
Choi, SJ
Date Issued
2002-01
Publisher
SPRINGER-VERLAG BERLIN
Abstract
In this paper, I introduce a concept of differential decorrelation which finds a linear mapping that minimizes the concurrent change of variables. Motivated by the differential anti-Hebbian rule [1], I develop a natural gradient algorithm for differential decorrelation and present its local stability analysis. The algorithm is successfully applied to the task of nonstationary source separation.
Keywords
LEARNING ALGORITHMS; SOURCE SEPARATION; NONSTATIONARY
URI
https://oasis.postech.ac.kr/handle/2014.oak/18649
DOI
10.1007/3-540-46084-5_189
ISSN
0302-9743
Article Type
Article
Citation
LECTURE NOTES IN COMPUTER SCIENCE, vol. 2415, page. 1168 - 1173, 2002-01
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최승진CHOI, SEUNGJIN
Dept of Computer Science & Enginrg
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