Global Asymptotical Stability for Neural Networks with Multiple Time-Varying Delays

  • Authors:

  • Jianlong Qiu;Jinde Cao;Zunshui Cheng

  • Affiliations:

  • Department of Mathematics, Southeast University, Nanjing 210096, China and Department of Mathematics, Linyi Normal University, Linyi 276005, China;Department of Mathematics, Southeast University, Nanjing 210096, China;Department of Mathematics, Southeast University, Nanjing 210096, China

  • Venue:
  • ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks
  • Year:
  • 2007

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Abstract

In this paper, the global uniform asymptotical stability is studied for neural networks with multiple time-varying delays by constructing appropriate Lyapunov-Krasovskii functional and using the linear matrix inequality (LMI) approach. The restriction on the derivative of the time-varying delay function ï戮驴ij(t) to be less than unit is removed by using slack matrix method. A numerical example is provided to demonstrate the effectiveness and applicability of the proposed criteria.