Self-control dynamics for sparsely coded networks with synaptic noise
Abstract
Description
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.
5 pages Latex, 1 ps and 4 eps figures, to appear in the proceedings of the 2004 International Joint Conference on Neural Networks, Budapest (IEEE)
5 pages Latex, 1 ps and 4 eps figures, to appear in the proceedings of the 2004 International Joint Conference on Neural Networks, Budapest (IEEE)