Parallel Dynamics of Continuous Hopfield Model Revisited

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  • Mimura Kazushi
    Graduate School of Information Sciences, Hiroshima City University

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Abstract

We have applied the generating functional analysis (GFA) to the continuous Hopfield model. We have also confirmed that the GFA predictions in some typical cases exhibit good consistency with computer simulation results. When a retarded self-interaction term is omitted, the GFA result becomes identical to that obtained using the statistical neurodynamics as well as the case of the sequential binary Hopfield model.

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