Memory retrieval in a neural network with chaotic neurons and dynamic synapses

Abstract

An associative neural network with chaotic neuron model and synaptic depression (CSDNN) is constructed. Memory switching phenomenon in the network is demonstrated. Simulation results show that with various parameter value settings and with various initial conditions, the memory retrieval frequency of CSDNN distributes uniformly among the stored patterns, and the rate of memory retrieval of CSDNN is much higher than that of a chaotic neural network. The possible utilization of memory retrieval in CSDNN is also discussed. © Springer-Verlag Berlin Heidelberg 2005.