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具有变时滞的Hopfield型神经网络的全局指数稳定性
引用本文:廖晓昕,肖冬梅. 具有变时滞的Hopfield型神经网络的全局指数稳定性[J]. 电子学报, 2000, 28(4): 87-90
作者姓名:廖晓昕  肖冬梅
作者单位:1. 华中理工大学控制科学与工程系,武汉,430074
2. 华中师范大学数学系,武汉,430074
基金项目:国家自然科学基金!(No .698740 1 6)资助课题,高等学校博士学科点专项基金!(No .970 4 872 2 )资助课题,国家“973项目”!(G1 9980 2
摘    要: 本文利用推广的Halanay时滞微分不等式和Lyapunov函数来研究具有可变时滞的Hopfield型神经网络的平衡状态的全局指数稳定性,得到了不依赖含任何未知函数存在性的简便代数判据,为实际应用提供方便.

关 键 词:Halanay不等式  神经网络  变时滞  全局指数稳定

Globally Exponential Stability of Hopfield Neural Networks with Time-varying Delays
LIAO Xiao-xin,XIAO Dong-mei. Globally Exponential Stability of Hopfield Neural Networks with Time-varying Delays[J]. Acta Electronica Sinica, 2000, 28(4): 87-90
Authors:LIAO Xiao-xin  XIAO Dong-mei
Affiliation:1. Department of Control Science and Engineering,Huazhong University of Science and Technology,Wuhan 430074,China;2. Department of Mathematics,Huazhong Normal University,Wuhan 430074,China
Abstract:Employing the extended Halanay's delay differential inequality and Lypunov functions,we study globally exponential stability of equilibrium states of Hopfield neural networks with time-varying delays.The results presented here are independent of any unknown function and are the algebraic oriteria entirely,which are obviously easy to be used.
Keywords:Halanay's inequality  neural networks  time-varying delay  globally exponential stability
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