具有分布时滞的双向联想记忆型Cohen-Grossberg神经网络的全局指数稳定性(英文)  

Global exponential stability of BAM type Cohen-Grossberg neural network with distributed delays

作　　者：张超龙[1] 杨逢建[1] 杨建富[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4期47-50,共4页Journal of Zhongkai University of Agriculture and Engineering

基　　金：Supported by National Natural Science Foundation of China(31071560);Natural Science Foundation of Guangdong Province(10151022501000004)

摘　　要：通过利用李雅普洛夫函数和Halanay不等式研究了具有分布时滞的双向联想记忆型Cohen-Grossberg神经网络,得到平衡点存在性及全局指数稳定性、全局鲁棒指数稳定性的充分条件,最后通过实例验证了结论.A class of the bidirectional associative memory ( BAM) type Cohen-Grossberg neural network with distributed delays was considered by Lyapunov function and Halanay inequality .Some sufficient con-ditions about the existence of equilibrium point , globally exponential stability and globally exponentially robust stability were obtained .At last, an example was given to demonstrated the results .

关 键 词：双向联想记忆型Cohen-Grossberg神经网络 稳定 分布时滞 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程]