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

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  • Xiaofeng Liao
  • Xiaofan Yang
  • Wei Zhang

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.

Suggested Citation

  • Xiaofeng Liao & Xiaofan Yang & Wei Zhang, 2006. "Delay-dependent asymptotic stability for neural networks with time-varying delays," Discrete Dynamics in Nature and Society, Hindawi, vol. 2006, pages 1-25, July.
    • Handle: RePEc:hin:jnddns:091725
    DOI: 10.1155/DDNS/2006/91725
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