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A unified learning algorithm to extract principal and minor components

Peng, Dezhong, Yi, Zhang and Xiang, Yong 2009, A unified learning algorithm to extract principal and minor components, Digital signal processing, vol. 19, no. 4, pp. 640-649.

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Title A unified learning algorithm to extract principal and minor components
Author(s) Peng, Dezhong
Yi, Zhang
Xiang, Yong
Journal name Digital signal processing
Volume number 19
Issue number 4
Start page 640
End page 649
Total pages 10
Publisher Academic Press
Place of publication Maryland Heights, Mo.
Publication date 2009-07
ISSN 1051-2004
1095-4333
Keyword(s) principal component analysis (PCA)
minor component analysis (MCA)
deterministic discrete time (DDT) system
eigenvalue
eigenvector
Summary Recently, many unified learning algorithms have been developed to solve the task of principal component analysis (PCA) and minor component analysis (MCA). These unified algorithms can be used to extract principal component and if altered simply by the sign, it can also serve as a minor component extractor. This is of practical significance in the implementations of algorithms. Convergence of the existing unified algorithms is guaranteed only under the condition that the learning rates of algorithms approach zero, which is impractical in many practical applications. In this paper, we propose a unified PCA & MCA algorithm with a constant learning rate, and derive the sufficient conditions to guarantee convergence via analyzing the discrete-time dynamics of the proposed algorithm. The achieved theoretical results lay a solid foundation for the applications of our proposed algorithm.
Language eng
Field of Research 090609 Signal Processing
Socio Economic Objective 890104 Mobile Telephone Networks and Services
HERDC Research category C1 Refereed article in a scholarly journal
ERA Research output type C Journal article
HERDC collection year 2009
Copyright notice ©2009, Elsevier Inc.
Persistent URL http://hdl.handle.net/10536/DRO/DU:30028080

Document type: Journal Article
Collection: School of Engineering
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