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Hopfield model with multistate neurons and its optoelectronic implementation

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Abstract

A Hopfield model with multistate neurons is described. This model is able to deal with multivalued problems such as restoring a degraded image with gray level equivalent to that produced by the two-states model, but needs many less neurons and interconnections. The performance of this model is compared with that of the linear model, and it is concluded that the multistate neuron model can produce convergence more quickly. Finally, a hybrid system for the implementation of this model is discussed.

© 1991 Optical Society of America

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