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