具可变时滞的细胞神经网络的周期解  

Periodic Solution of Cellular Neural Networks with Time-varying Delay

作　　者：谢惠琴[1] 王全义[2] 

机构地区：[1]福州大学数学系,福建福州350002 [2]华侨大学数学系,福建泉州362011

出　　处：《泉州师范学院学报》2004年第2期31-36,共6页Journal of Quanzhou Normal University

基　　金：国务院侨务办公室科研基金资助项目(01QZR02)

摘　　要：研究具可变时滞的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(i=1,2,…,n),并结合变量替换及一些分析技巧,给出一些新的充分准则.这些准则可用于设计全局指数稳定的和周期振荡的具可变时滞的神经网络,扩大了神经网络设计范围.In this paper, we study the existence and the global exponential stability of periodic solution for cellular neural networks with time-varying delays. By ingeniously importing real parameters d_i>0(i=1,2,…,n) which can be adjusted, using the method of variation of parameters and some analysis techniques, some new sufficient conditions are established. These conditions can be used to design globally exponentially stable and periodical oscillatory neural networks with time-varying delays. And they greatly enlarge the area of designing neural networks. This has important significance in both theory and application.

关 键 词：周期解 全局指数稳定性 可变时滞 细胞神经网络 存在性 

分 类 号：O175.1[理学—数学]