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Neural Computation

July 1994, Vol. 6, No. 4, Pages 739-747
(doi: 10.1162/neco.1994.6.4.739)
© 1994 Massachusetts Institute of Technology
Stability of Oja's PCA Subspace Rule
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Abstract

This paper deals with stability of Oja's symmetric algorithm for estimating the principal component subspace of the input data. Exact conditions are derived for the gain parameter on which the discrete algorithm remains bounded. The result is extended for a nonlinear version of Oja's algorithm.