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Discrete Dynamics in Nature and Society
Volume 2006, Article ID 91725, 25 pages

Delay-dependent asymptotic stability for neural networks with time-varying delays

1School of Computer and Information, Chongqing Jiaotong University, Chonqing 400074, China
2Department of Computer, Science and Engineering, Chongqing University, Chongqing 400030, China
3Department of Computer and Modern Education Technology, Chongqing Education College, Chongqing 400030, China

Received 3 August 2005; Accepted 6 November 2005

Copyright © 2006 Xiaofeng Liao et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


We study the dynamical behavior of a class of neural network models with time-varying delays. By constructing suitable Lyapunov functionals, we obtain sufficient delay-dependent criteria to ensure local and global asymptotic stability of the equilibrium of the neural network. Our results are applied to a two-neuron system with delayed connections between neurons, and some novel asymptotic stability criteria are also derived. The obtained conditions are shown to be less conservative and restrictive than those reported in the known literature. Some numerical examples are included to demonstrate our results.