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Subspace independent component analysis using vector kurtosis

Sharma, Alokanand and Paliwal, K.K. (2006) Subspace independent component analysis using vector kurtosis. Pattern Recognition, 39 . pp. 2227-2232. ISSN 0031-3203

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    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.

    Item Type: Journal Article
    Subjects: T Technology > TA Engineering (General). Civil engineering (General)
    Divisions: Faculty of Science, Technology and Environment (FSTE) > School of Engineering and Physics
    Depositing User: Alokanand Sharma
    Date Deposited: 10 Aug 2006 11:43
    Last Modified: 07 Oct 2013 16:05
    URI: http://repository.usp.ac.fj/id/eprint/5028
    UNSPECIFIED

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