GLOBAL ATTRACTIVITY AND GLOBAL EXPONENTIAL STABILITY FOR DELAYED HOPFIELD NEURAL

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

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.

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作 者: 蒲志林 徐道义  
作者单位:蒲志林(Department of Mathematics, Sichuan Normal University, Chengdu 610066, P R China;Department of Mathematics, Sichuan University, Chengdu 610064, P R China)
bh{#o Mb`0徐道义(Department of Mathematics, Sichuan University, Chengdu 610064, P R China) 
刊 名:应用数学和力学(英文版)  EI SCI
英文刊名:APPLIED MATHEMATICS AND MECHANICS(ENGLISH EDITION) 
年,卷(期):2001 22(6) 
分类号:TN911.23 O332 
关键词:neural networks   global attractivity   global exponential stability  
机标关键词:HOPFIELD NEURAL NETWORKglobal exponential stabilityglobal attractivityHopfield neural networksLiapunov functiontime delays 
基金项目:国家自然科学基金,Sichua Education Committee 
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