含有双时滞量的细胞神经网络的指数稳定性  

Globally Exponential Stability of Cellular Neural Networks with Two Delays

作　　者：董彪 蒋自国 DONG Biao;JIANG Zi-guo(College of Mathematics and Computer Science,Aba Teachers University,Wenchuan 623002,China;Institute of Mathematics,Aba Teachers University,Wenchuan 623002,China)

机构地区：[1]阿坝师范学院数学与计算机科学学院,四川汶川632002 [2]阿坝师范学院数学研究所,四川汶川632002

出　　处：《数学的实践与认识》2018年第20期299-303,共5页Mathematics in Practice and Theory

基　　金：四川省教育厅自然科学基金(15ZA0337);四川高等学校科研创新团队项目计划(18TD0047);阿坝师范学院重点课题(ASB15-22,ASA12-22,ASA13-14)

摘　　要：讨论了一类含有双时滞量的细胞神经网络模型在平衡点的全局指数稳定性问题．通过构造Lyapunov函数，根据Young不等式和Halanay含时滞的微分不等式，在不需要激励函数满足全局Lipschitz条件的情况下，得到了含有双时滞量的细胞神经网络模型在平衡点是全局指数稳定性的一个充分条件的判据．其所得结果包含并改进了原有的结论，并举例说明了该结果的有效性．The main purpose is to study the globally exponential stability of the equilibrium point for a class of cellular neural networks with two delays, without assuming global Lipschitz conditions on the activation functions, applying idea of vector Lyapunov function, combining Young inequality and Halanay differentionl inequality with delay, some sufficient conditions for globally exponentionl stability of neural networks are obtained. The present results include and improve some old ones. As an illustration, a example is worked out using the results obtained

关 键 词：细胞神经网络 时滞 全局指数稳定性 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程]