Potts-glass models of neural networks

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Abstract

The theory of neural networks is extended to include discrete neurons with more than two discrete states. The dynamics of such systems are studied. The maximum number of storage patterns is found to be proportional to Nq(q-1), where q is the number of Potts states and N is the size of the network. The properties of the Potts neural network are compared with the Ising case, and the similarity between the Potts neural network and a diluted multineuron interacting Hopfield model is discussed.

Original languageEnglish
Pages (from-to)2739-2742
Number of pages4
JournalPhysical Review A
Volume37
Issue number7
DOIs
StatePublished - 1988

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