Journal of Mathematical Biology

, Volume 15, Issue 3, pp 267–273 | Cite as

Simplified neuron model as a principal component analyzer

  • Erkki Oja


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 


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Copyright information

© Springer-Verlag 1982

Authors and Affiliations

  • Erkki Oja
    • 1
  1. 1.Institute of MathematicsUniversity of KuopioKuopio 10Finland

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