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Abstract:
We study several statistically and biologically motivated
learning rules using the same visual environment and neuronal
architecture. This allows us to concentrate on the feature
extraction and neuronal coding properties of these rules. We find
that the quadratic form of the BCM rule behaves in a manner similar
to a kurtosis maximization rule when the distribution contains
kurtotic directions, although the BCM modification equations are
computationally simpler.
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