arXiv:cond-mat/0303425AbstractReferencesReviewsResources
Mean-field dynamics of sequence processing neural networks with finite connectivity
Published 2003-03-20Version 1
A recent dynamic mean-field theory for sequence processing in fully connected neural networks of Hopfield-type (During, Coolen and Sherrington, 1998) is extended and analized here for a symmetrically diluted network with finite connectivity near saturation. Equations for the dynamics and the stationary states are obtained for the macroscopic observables and the precise equivalence is established with the single-pattern retrieval problem in a layered feed-forward network with finite connectivity.
Comments: 16 pages Latex
Journal: Physica A 328, 1-12 (2003)
Keywords: sequence processing neural networks, finite connectivity, mean-field dynamics, dynamic mean-field theory, fully connected neural networks
Tags: journal article
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