Article,

Simplified neuron model as a principal component analyzer

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Journal of Mathematical Biology, 15 (3): 267--273 (Nov 1, 1982)
DOI: 10.1007/BF00275687

Abstract

A simple linear neuron model with constrained Hebbian-type synaptic modification is analyzed and a new class of unconstrained learning rules is derived. It is shown that the model neuron tends to extract the principal component from a stationary input vector sequence.

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