一类随机离散神经网络全局渐近同步  

Synchronization of a class of uncertain stochastic discrete-time delayed neural networks

作　　者：陈忠[1] 黄优良[1] 

机构地区：[1]韶关学院数学与信息科学学院,广东韶关512005

出　　处：《福州大学学报（自然科学版）》2012年第2期198-203,共6页Journal of Fuzhou University(Natural Science Edition)

基　　金：广东省自然科学基金资助项目(0314957301275);广东省韶关学院科研资助项目(20120102)

摘　　要：研究离散型时滞随机神经网络的同步问题,考虑了参数不确定性,解决离散型分布时滞对神经网络同步问题的影响.基于主从同步的概念,设计一个有更广泛应用的控制器,应用Lyapunov稳定性理论和线性矩阵不等式工具箱,得到这类神经网络同步的充分性判据.最后给出实际例子,检验了判据的有效性.The global asymptotical synchronization problem is discussed for a general class of uncertain stochastic discrete - time neural networks with time delay in this paper. Time delays include time - va- rying delay and distributed delay. A better controller is designed for synchronization. Based on the drive- response concept and the Lyapunov stability theorem, a linear matrix inequality （LMI） ap- proach is exploited to establish sufficient conditions under which the considered neural networks are globally asymptotically synchronized in the mean square.

关 键 词：神经网络 离散时滞 分布时滞 随机动力系统 同步 

分 类 号：O415[理学—理论物理]