The Hopfield Model with Multi-Level Neurons

Part of Neural Information Processing Systems 0 (NIPS 1987)

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Authors

Michael Fleisher

Abstract

The Hopfield neural network. model for associative memory is generalized. The generalization

replaces two state neurons by neurons taking a richer set of values. Two classes of neuron input output

relations are developed guaranteeing convergence to stable states. The first is a class of "continuous" rela-

tions and the second is a class of allowed quantization rules for the neurons. The information capacity for

networks from the second class is fOWld to be of order N 3 bits for a network with N neurons.

A generalization of the sum of outer products learning rule is developed and investigated as well.

© American Institute of Physics 1988

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