Modified Oja‘s Algorithms For Principal Subspace and Minor Subspaceextraction

Authors:
Tianping Chen
Affiliations:
Department of Mathematics, Fudan University, 200433 Shanghai, China. E-mail: tchen@fudan.sh.cn
Venue:
Neural Processing Letters
Year:
1997

Citing 3
Cited 0

Original Contribution: Principal components, minor components, and linear neural networks

Neural Networks
Time-domain solutions of Oja's equations

Neural Computation
Global convergence of Oja's subspace algorithm for principal component extraction

IEEE Transactions on Neural Networks

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Abstract

Principal component extraction and minor component extraction are well known and powerful techniques in time series.Modified Oja‘s algorithms for extracting principal and minor component subspaces are proposed. The only difference between them is the sign of the firstterm in the iteration equations. Simulations show that the algorithms are effective.