Subspace independent component analysis using vector kurtosis

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Title Subspace independent component analysis using vector kurtosis
Author Sharma, Alokanand; Paliwal, Kuldip Kumar
Journal Name Pattern Recognition
Year Published 2006
Place of publication United Kingdom
Publisher Pergamon
Abstract This discussion presents a new perspective of subspace independent component analysis (ICA). The notion of a function of cumulants (kurtosis) is generalized to vector kurtosis. This vector kurtosis is utilized in the subspace ICA algorithm to estimate subspace independent components. One of the main advantages of the presented approach is its computational simplicity. The experiments have shown promising results in estimating subspace independent components.
Peer Reviewed Yes
Published Yes
Publisher URI http://www.elsevier.com/wps/find/journaldescription.cws_home/328/description#description
Alternative URI http://dx.doi.org/10.1016/j.patcog.2006.04.021
Volume 39
Page from 2227
Page to 2232
ISSN 0031-3203
Date Accessioned 2007-03-18
Language en_AU
Research Centre Institute for Integrated and Intelligent Systems
Faculty Faculty of Science, Environment, Engineering and Technology
Subject PRE2009-Pattern Recognition
URI http://hdl.handle.net/10072/14346
Publication Type Journal Articles (Refereed Article)
Publication Type Code c1

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