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一类变时滞神经网络的全局指数稳定性
引用本文:张丽娟,斯力更.一类变时滞神经网络的全局指数稳定性[J].应用数学,2007,20(2):258-262.
作者姓名:张丽娟  斯力更
作者单位:1. 烟台大学数学与信息科学学院,山东,烟台,264005
2. 内蒙古师范大学数学系,内蒙,呼和浩特,010022
基金项目:国家自然科学基金;烟台大学校科研和教改项目
摘    要:本文研究一类变时滞神经网络平衡点的全局指数稳定性.在不要求激活函数全局Lipschitz条件下,利用Lyapunov函数方法,并结合Young不等式和Halanay时滞微分不等式,得到了系统全局指数稳定的充分条件.文末,一个数值例子用以说明本文结果的有效性.

关 键 词:神经网络  变时滞  全局指数稳定性
文章编号:1001-9847(2007)02-0258-05
修稿时间:2006-05-15

Globally Exponential Stability of a Class of Neural Networks with Variable Delays
ZHANG Li-juan,SI Li-geng.Globally Exponential Stability of a Class of Neural Networks with Variable Delays[J].Mathematica Applicata,2007,20(2):258-262.
Authors:ZHANG Li-juan  SI Li-geng
Institution:1. School of Mathematics and Information Science, Yantai University, Yantai 264005, China ; 2. Department of Mathematics, Inner Mongolia Normal University , Huhhot 010020, China
Abstract:The main purpose of this paper is to study the globally exponential stability of the equilibrium point for a class of neural networks with time-varying delays.Without assuming global Lipschitz conditions on the activation functions,applying idea of vector Lyapunov function,combining Young inequality and Halanay differential inequality with delay,the sufficient conditions for globally exponential stability of neural networks are obtained.As an illustration,a numerical example is worked out using the results obtained.
Keywords:Neural networks  Time-varying delay  Globally exponential stability
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