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Int J Neural Syst. 2004 Feb;14(1):1-8.

A self-stabilizing learning rule for minor component analysis.

Author information

1
Computer Engineering Group, Faculty of Technology, Bielefeld University, D-33594 Bielefeld, Germany. moeller@techfak.uni-bielefeld.de

Abstract

The paper reviews single-neuron learning rules for minor component analysis and suggests a novel minor component learning rule. In this rule, the weight vector length is self-stabilizing, i.e., moving towards unit length in each learning step. In simulations with low- and medium-dimensional data, the performance of the novel learning rule is compared with previously suggested rules.

PMID:
15034943
DOI:
10.1142/S0129065704001863
[Indexed for MEDLINE]

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