USP Electronic Research Repository

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

PDF - Accepted Version
Download (355kB) | Preview


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: 09 Aug 2006 23:43
Last Modified: 07 Oct 2013 04:05

Actions (login required)

View Item View Item

Document Downloads

More statistics for this item...