GLOBAL EXPONENTIAL STABILITY OF HOPFIELD NEURAL NETWORKS WITH VARIABLE DELAYS AND IMPULSIVE EFFECTS

作     者：杨志春 徐道义 

作者机构：Mathematics CollegeChongqing Normal UniversityChongqing 400047P. R. China Yangtze Center of MathematicsSichuan UniversityChengdu 610064P. R. China Yangtze Center of MathematicsSichuan UniversityChengdu 610064P. R. China 

出 版 物：《Applied Mathematics and Mechanics(English Edition)》 (应用数学和力学（英文版）)

年 卷 期：2006年第27卷第11期

页      面：1517-1522页

核心收录：

学科分类：07[理学] 070104[理学-应用数学] 0805[工学-材料科学与工程（可授工学、理学学位）] 0802[工学-机械工程] 0701[理学-数学] 0801[工学-力学（可授工学、理学学位）] 

基　　金：Project supported by the National Natural Science Foundation of China (No. 10371083) 

主　　题：neural networks impulse delay stability 

摘      要：A class of Hopfield neural network with time-varying delays and impulsive effects is concerned. By applying the piecewise continuous vector Lyapunov function some sufficient conditions were obtained to ensure the global exponential stability of impulsive delay neural networks. An example and its simulation are given to illustrate the effectiveness of the results.