Global asymptotically robust stability of cellular neural networks with time-varying delay

  • Authors:

  • Xue-Li Wu;Zhantong Zhou;Wen-Xia Du;Yang Li

  • Affiliations:

  • Hebei University of Science and Technology, Shijiazhuang, Engineering Technology Research Centre, Hebei Province and YanShan University, Qinhuangdao;Hebei University of Science and Technology, Shijiazhuang, Engineering Technology Research Centre, Hebei Province;YanShan University, Qinhuangdao and Hebei Normal University, Shijiazhuang;Hebei University of Science and Technology, Shijiazhuang, Engineering Technology Research Centre, Hebei Province

  • Venue:
  • CCDC'09 Proceedings of the 21st annual international conference on Chinese control and decision conference
  • Year:
  • 2009

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Abstract

Time-delay is frequently encountered in neural networks, and it is often a source of instability and oscillations in a system. It is very important to research the stability of delayed neural network, especially for global asymptotically robust stability of the neural network with time-varying delay. In the letter, a novel method is proposed in this note for global asymptotically robust stability of cellular neural networks with time-varying delay. New delay-dependent global asymptotically robust stability conditions of cellular neural network with time-varying delay is presented by constructing Lyapunov function and using linear matrix inequality (LMI). Finally, numerical examples are given to demonstrate the effect of the proposed method.