Simplified Neuron Model as a Principal Component Analyzer.¶
Oja, E. (1982). Simplified Neuron Model as a Principal Component Analyzer. Journal of Mathematical Biology, 15(3), 267-273.
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1 citation across 1 artifact.
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Primes¶
- Hebbian Learning
- Hebb's biological rule explicitly inspired early artificial neural networks, and its normalizing variant travels into principal-component analysis; the local-update commitment also motivates the contemporary search for biologically plausible alternatives to backpropagation.
This sourceAdds a normalizing term to the Hebbian rule so the weight vector stays bounded and converges to the leading eigenvector of the input covariance (the first principal component).
- Hebb's biological rule explicitly inspired early artificial neural networks, and its normalizing variant travels into principal-component analysis; the local-update commitment also motivates the contemporary search for biologically plausible alternatives to backpropagation.
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