Journal of Mathematical Biology

, Volume 15, Issue 3, pp 267–273

Simplified neuron model as a principal component analyzer

Authors

  • Erkki Oja
    • Institute of MathematicsUniversity of Kuopio
Article

DOI: 10.1007/BF00275687

Cite this article as:
Oja, E. J. Math. Biology (1982) 15: 267. 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.

Key words

Neuron models Synaptic plasticity Stochastic approximation

Copyright information

© Springer-Verlag 1982