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

Authors:
Zhijie Wang;Hong Fan
Affiliations:
College of Information Science and Technology, Donghua University, Shanghai, China;Glorious sun School of Business and Management, Donghua University, Shanghai, China
Venue:
IWANN'05 Proceedings of the 8th international conference on Artificial Neural Networks: computational Intelligence and Bioinspired Systems
Year:
2005

Citing 4
Cited 2

Chaotic simulated annealing by a neural network model with transient chaos

Neural Networks
Associative dynamics in a chaotic neural network

Neural Networks
Pulsed neural networks

Pulsed neural networks
Associative memory with dynamic synapses

Neural Computation

Dynamics of a continuous-valued discrete-time Hopfield neural network with synaptic depression

Neurocomputing
A New Associative Model with Dynamical Synapses

Neural Processing Letters

Quantified Score

Hi-index	0.00

Visualization

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.