Self-control dynamics for sparsely coded networks with synaptic noise

Details Self-control dynamics for sparsely coded networks with synaptic noise Self-control dynamics for sparsely coded networks with synaptic noise

2004-03-23

arxiv.org/abs/cond-mat/0403576v1

Physics

Condensed Matter

Disordered Systems and Neural Networks

5 pages Latex, 1 ps and 4 eps figures, to appear in the proceedings of the 2004 International Joint Conference on Neural Netwo

Scientific paper

For the retrieval dynamics of sparsely coded attractor associative memory models with synaptic noise the inclusion of a macroscopic time-dependent threshold is studied. It is shown that if the threshold is chosen appropriately as a function of the cross-talk noise and of the activity of the memorized patterns, adapting itself automatically in the course of the time evolution, an autonomous functioning of the model is guaranteed. This self-control mechanism considerably improves the quality of the fixed-point retrieval dynamics, in particular the storage capacity, the basins of attraction and the mutual information content.

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