一类时延细胞神经网络的周期解  

Periodic solution for a class of cellular neural networks with delays

作　　者：谢惠琴[1] 王全义[2] 

机构地区：[1]福州大学数学与计算机科学学院,福建福州350002 [2]华侨大学数学系,福建泉州362011

出　　处：《福州大学学报（自然科学版）》2004年第2期127-131,共5页Journal of Fuzhou University(Natural Science Edition)

基　　金：国务院侨务办公室科研基金资助项目(01QZR02)

摘　　要：引入可调实参数di>0(i=1,2,…,n),通过构造Lyapunov泛函,结合一些分析技巧,对一类时延细胞神经网络周期解的存在性和全局指数稳定性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时滞的神经网络.By ingeniously importing real parameters d_i>0(i=1, 2, ..., n) which can be adjusted, making use of the Lyapunov functional method and some analysis techniques, some new sufficient conditions for the existence of periodic solution and global exponential stability for cellular neural networks with delays are established. These conditions can be used to design globally exponentially stable and periodical oscillatory neural networks with delays.

关 键 词：细胞神经网络 LYAPUNOV泛函 周期解 全局指数稳定性 

分 类 号：O175.1[理学—数学]