Mean-field dynamics of sequence processing neural networks with finite connectivity

Details Mean-field dynamics of sequence processing neural networks with finite connectivity Mean-field dynamics of sequence processing neural networks with finite connectivity

2003-03-20

arxiv.org/abs/cond-mat/0303425v1

Physica A 328, 1-12 (2003)

Physics

Condensed Matter

Disordered Systems and Neural Networks

16 pages Latex

Scientific paper

10.1016/S0378-4371(03)00569-7

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.

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