Chaos synchronization for bi-directional coupled two-neuron systems with discrete delays

Authors:
Xiaohong Zhang;Shangbo Zhou
Affiliations:
School of Software Engineering, Chongqing University, China;Department of Computer Science and Engineering, Chongqing University, China
Venue:
ISNN'05 Proceedings of the Second international conference on Advances in Neural Networks - Volume Part I
Year:
2005

Citing 8
Cited 1

Chaos and asymptotical stability in discrete-time neural networks

Physica D
Associative dynamics in a chaotic neural network

Neural Networks
Synchronized chaos and other coherent states for two coupled neurons

Physica D
Bifurcation analysis on a two-neuron system with distributed delays

Physica D
Controlling chaos in a chaotic neural network

Neural Networks
Bifurcation analysis on a two-neuron system with distributed delays

Neural Networks
Convergence under dynamical thresholds with delays

IEEE Transactions on Neural Networks
Asymptotic stability criteria for a two-neuron network with different time delays

IEEE Transactions on Neural Networks

Global exponential stability in Lagrange sense for neutral type recurrent neural networks

Neurocomputing

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper, the chaos synchronization between two delayed neuron chaotic systems with linearly bi-directional coupling is investigated. Some generic criterion is developed for choosing the appropriate coupling parameters to ensure global chaos synchronization based on Krasovskii-Lyapunov theory. Finally, numerical results illustrate the effectiveness of the criterion.