Global Exponential Stability for a Class of Generalized Cellular Neural Networks with Multi-proportional Delays

摘要：

对一类具多比例时滞广义细胞神经网络的全局指数稳定性进行研究.首先用Brouwer不动点定理证明了该系统平衡点的存在唯一性,再通过建立时滞微分不等式,获得了保证该系统平衡点全局指数稳定的时滞独立的充分条件.最后,给出了一个数值算例验证所得结果的正确性和有效性.

A class of generalized cellular neural networks with multi-proportional delays is studied. At first, the exist- ence and uniqueness of equilibrium of the＇ system are certified by the Brouwer fixed point theorem. Then by establishing a de- layed differential inequality, a delay-independent sufficient condition is obtained for guaranteeing the global exponential stability of equilibrium of the system. Finally, we used an example and its simulation to demonstrate the correctness and effectiveness of the results.

作者：

刘学婷 周立群

机构地区：

天津师范大学数学科学学院

出处：

《betway官方app 学报：自然科学版》 CAS 北大核心 2016年第4期143-150,共8页

基金：

国家自然科学基金(61374009)

关键词：

广义细胞神经网络 全局指数稳定性 比例时滞 LYAPUNOV泛函 时滞微分不等式

generalized cellular neural networks global exponential stability proportional delay Lyapunov functional delayed differential inequality

分类号：

O175.1 [理学—基础数学]

一类具多比例时滞广义细胞神经网络的全局指数稳定性.pdf