带脉冲和时滞的时标双向联想记忆Cohen-Grossberg神经网络的稳定性分析(英文)  

Stability analysis of impulsive BAM type Cohen-Grossberg neural networks with delays on time scales

作　　者：杨逢建[1] 张超龙[1] 吴东庆[1] 杨建富[1] 王前[1] 

机构地区：[1]仲恺农业工程学院计算科学学院,广东广州510225

出　　处：《仲恺农业工程学院学报》2013年第1期38-43,共6页Journal of Zhongkai University of Agriculture and Engineering

基　　金：Supported by Science and Technology Plan Foundation of Guangzhou under Grant(2006j1-C0341)

摘　　要：讨论了一类带脉冲和时滞的含有可变系数的时标双向联想记忆Cohen-Grossberg神经网络的稳定性.利用Lyapunov泛函和Halanay不等式,获得了这类神经网络的平衡点的存在性、全局指数稳定性、全局指数鲁棒稳定性,表明脉冲对于系统的指数稳定性和鲁棒稳定性起了重要的作用.最后以实例说明了理论结果的有效性.A class of impulsive bidirectional associative memories neural networks that possessed a Cohen-Grossberg dynamics incorporates time delays and variable coefficients on time scales was considered. The existence of equilibrium point, globally exponential stability and globally exponentially robust stability were investigated by Lyapunov function and Halanay inequality. It was proved that impulses did contribution to the exponential stability and robust stability. An illustrative example was given to demonstrate the effectiveness of the obtained results.

关 键 词：脉冲 时滞 指数稳定性 鲁棒稳定性 时标 

分 类 号：O175[理学—数学]