Discrete Dynamics in Nature and Society
Volume 2006 (2006), Issue 3, Article ID 91725, 25 pages
doi:10.1155/DDNS/2006/91725
Delay-dependent asymptotic stability for neural networks with time-varying delays
Xiaofeng Liao1
, Xiaofan Yang1
and Wei Zhang3
1School of Computer and Information, Chongqing Jiaotong University, Chonqing 400074, China
3Department of Computer and Modern Education Technology, Chongqing Education College, Chongqing 400030, China
Abstract
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.