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Fast principal component analysis using fixed-point algorithm

Sharma, Alokanand and Paliwal, K.K. (2007) Fast principal component analysis using fixed-point algorithm. Pattern Recognition Letters, 28 (10). pp. 1151-1155. ISSN 0167-8655

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Abstract

In this paper we present an efficient way of computing principal component analysis (PCA). The algorithm finds the desired number of leading eigenvectors with a computational cost that is much less than that from the eigenvalue decomposition (EVD) based PCA method. The mean squared error generated by the proposed method is very similar to the EVD based PCA method.

Item Type: Journal Article
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Science, Technology and Environment (FSTE) > School of Engineering and Physics
Depositing User: Ms Mereoni Camailakeba
Date Deposited: 25 May 2007 16:17
Last Modified: 18 Jul 2012 14:07
URI: http://repository.usp.ac.fj/id/eprint/837
UNSPECIFIED

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