Probabilistic Networks

Abstract

One of the problems with the Hopfield network is its tendency to settle at local energy minima rather than at the global minimum. Some of the local minima represent points in the ‘energy landscape’ where the stored patterns can be found. When an input vector is applied to the network, if it lies close to one of these minima, it will move towards that minima because of the nature of the changes in the neurons, which always lower the energy in the network. So if a pattern is close to one of the stored patterns, it should produce that stored pattern at the output, once it has settled in the local minima.

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