Applied Mathematics and Mechanics (English Edition) ›› 2001, Vol. 22 ›› Issue (6): 711-716.

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GLOBAL ATTRACTIVITY AND GLOBAL EXPONENTIAL STABILITY FOR DELAYED HOPFIELD NEURAL NETWORK MODELS

PU Zhi-lin1,2, XU Dao-yi 2   

  1. 1. Department of Mathematics, Sichuan Normal University, Chengdu 610066, P.R.China;
    2. Department of Mathematics, Sichuan University, Chengdu 610064, P.R.China
  • Received:1999-11-23 Revised:2000-05-16 Online:2001-06-18 Published:2001-06-18
  • Supported by:
    the National Natural Science Foundation of China (19771059);the Science Foundation of the Sichua Education Committee

Abstract: Some global properties such as global attractivity and global exponential stability for delayed Hopfield neural networks model, under the weaker assumptions on nonlinear activation functions, are concerned. By constructing suitable Liapunov function, some simpler criteria for global attractivity and global exponential stability for Hopfield continuous neural networks with time delays are presented.

2010 MSC Number: 

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