GLOBAL ROBUST STABILITY OF INTERVAL HOPFIELD NEURAL NETWORKS WITH CONTINUOUSLY DISTRIBUTED DELAYS

作     者：Kao Yonggui Gao Cunchen Liu Guanfeng 

作者机构：Dept. of Math. Ocean University of China Qingdao 266071 China Dept. of Math. Zaozhuang University Zaozhuang 277160 Shandong College of Resources and Environment EngineeringWuhan University of Science and Technology Wuhan 430081 

出 版 物：《Annals of Differential Equations》 (微分方程年刊（英文版）)

年 卷 期：2007年第23卷第4期

页      面：427-432页

学科分类：07[理学] 070104[理学-应用数学] 0701[理学-数学] 

基　　金：the National Natural Science Foundation of China under grant 60674020 the Natural Science Foundation of Shandong under grant Z2006G11 

主　　题：global robust stability neural networks distributed delays topological degree 

摘      要：In this paper, we implement topological degree theory and Lyapunov-functional methods to obtain the existence and uniqueness of the equilibrium point and its global robust stability for interval Hopfield neural networks with continuously distributed delays. Moreover, the methods used in judging the robust stability are proven practical and easily verifiable.