DYNAMICS OF NEURAL NETWORKS WITH NONMONOTONIC NEURONS AND ADAPTING SYNAPSES

We study a strongly diluted neural network with nonmonotonic neurons a nd adapting synapses, whose dynamics can be analytically calculated. D ynamics reduction is observed for low connectivity: the network has no chaotic attractors in the stationary regime. For high connectivity ch aos is not completely removed. We present some evidence that the dynam ics reduction occurs, in the high connectivity case, when the synaptic correlations become relevant. (C) 1998 Published by Elsevier Science B.V.