具有时滞的细胞神经网络模型的全局指数稳定性  

Global Exponential Stability of Cellular Neural Networks with Time Delay

作　　者：宋乾坤[1] 

机构地区：[1]湖州师范学院数学系,浙江湖州313000

出　　处：《生物数学学报》2003年第4期433-438,共6页Journal of Biomathematics

基　　金：四川省教委青年基金(1998162);浙江省教育厅科研项目(20020304)

摘　　要：利用拓扑度理论、推广的Halanaly矩阵时滞微分不等式、Lyapunov原理以及Dini导数,研究了具有时滞的细胞神经网络模型的全局指数稳定性.去掉了有关文献中要求输出函数f_j在实数集R上有界、可微的条件,给出了更弱的判定平衡点的存在唯一性以及全局指数稳定性的判据,推广和改进了前人的相关结论,最后的数值例子说明本文结果不仅保守性小,而且计算简单.The global exponential stability of cellular neural networks with time Delay is investigated by the use of topological degree, the extended Halanay's matrix delay differential inequality, the Lyapunov functional method, and Dini's derivative. Two theorems and three corollaries are obtained, in which the boundedness and differentiability of output fi on real number set R in some articles are deleted. Some sufficient conditions for the existence of global exponential stable equilibrium of the networks in this paper are better than the sufficient conditions in quoted articles.

关 键 词：细胞神经网络 时滞 平衡点 全局指数稳定 拓扑度 DINI导数 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程] O175.12[自动化与计算机技术—控制科学与工程]