Global Asymptotic Synchronization of a Class of BAM Neural Networks with Time Delays via Integrating Inequality Techniques  

作　　者：LIN Feng ZHANG Zhengqiu 

机构地区：[1]Tourism College of Beijing Union University,Beijing 100101,China [2]College of Mathematics and Econometrics,Hunan University,Changsha 410082,China

出　　处：《Journal of Systems Science & Complexity》2020年第2期366-382,共17页系统科学与复杂性学报（英文版）

摘　　要：In this paper,the authors are concerned with global asymptotic synchronization for a class of BAM neural networks with time delays.Instead of using Lyapunov functional method,LMI method and matrix measure method which are recently widely applied to investigating global exponential/asymptotic synchronization for neural networks,two novel sufficient conditions on global asymptotic synchronization of above BAM neural networks are established by using a kind of new study method of global synchronization:Integrating inequality techniques.The method and results extend the study of global synchronization of neural networks.

关 键 词：A class of BAM neural networks with time delays global asymptotic synchronization integrating inequality techniques 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程] O231[自动化与计算机技术—控制科学与工程]