变时滞神经网络指数同步性的LMI新条件  

New LMI conditions for exponential synchronization of neural networks with time-varying delays

作　　者：范颖[1] 谭满春[1] 

机构地区：[1]暨南大学数学系,广州510632

出　　处：《计算机工程与应用》2011年第34期64-67,共4页Computer Engineering and Applications

基　　金：广东省自然科学基金(No.9151001003000005);广东省科技计划项目(No.2009B011400046)

摘　　要：研究了一类具有变时滞的非线性混沌神经网络的指数同步性问题。应用线性矩阵不等式和Lyapunov泛函方法,得到了具有驱动-响应结构的神经网络的指数同步性准则,建立了判断神经网络同步性的新的充分条件。通过实例说明了该方法的可行性和有效性。The exponential synchronization is investigated for a class of chaotic nonlinear neural networks with time-varying delays.Based on Lyapunov functional method and linear matrix inequality approach,the exponential synchronization criteria of the derive-response structure of neural networks are obtained,some new sufficient conditions are established for the exponential synchronization of neural networks.One example is given to illustrate the feasibility and effectiveness of the results.

关 键 词：神经网络 同步性 LYAPUNOV泛函 线性矩阵不等式 变时滞 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]