时延细胞神经网络的指数稳定性和周期解  

Exponential Stability and Periodic Solution for Cellular Neural Networks with Time Delay

作　　者：谢惠琴[1] 王全义[1] 

机构地区：[1]华侨大学数学系,福建泉州362011

出　　处：《华侨大学学报（自然科学版）》2004年第1期22-25,共4页Journal of Huaqiao University(Natural Science)

基　　金：国务院侨务办公室科研基金资助项目 (0 1QZR0 2 )

摘　　要：研究时延细胞神经网络周期解的存在性和全局指数稳定性问题 .巧妙地引入可调实参数di>0 (1 ,2 ,… ,n) ,通过构造Lyapunov泛函并结合有效的分析技巧 ,给出新的充分准则 .所得的结果 ,推广和改进已有报道的相关结果 .这些准则可用于设计全局指数稳定的和周期振荡的具时滞的神经网络 ,扩大神经网络设计的范围 .A study is made on the existence of periodic solution and globally exponential stability of cellular neural network with time delay. Some new sufficient criteria are given by ingeniously leading adjustable real parameters d i>0(i=1,2,...,n ), and by constructing lyapunov functional in combination with some skills of analysis. With the authors' results, the related results in the reported literatures can be entended and improved. These criteria can be applied to the design of globally exponential stable and periodically oscillatory neural network with time delay. They broaden the design of neural network.

关 键 词：时延细胞神经网络 周期解 全局指数稳定性 LYAPUNOV泛函 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程] O175.1[自动化与计算机技术—控制科学与工程]