学术
一类变时滞神经网络的全局指数稳定性
张丽娟[1] 斯力更[2]
[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
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。[著者文摘]
文章出处:
《应用数学》-2007年20卷2期 -258-262页
分 类 号:
文献标识码:
A
文章编号:
1001-9847（2007）02-0258-05
Globally Exponential Stability of a Class of Neural Networks with Variable Delays
ZHANG Li-juan, SI Li-geng（ 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 snfficient conditions for globally exponential stability of neural networks are obtained. As an illustration,a numerical example is worked out using the results obtained.[著者文摘]
Key words:
Neural networks ; Time-varying delay ; Globally exponential stability
基金资助:
Supported by National Natural Science Foundation of China （10461006） and the Youth Foundation of Yantai University（02037）
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