基于LMI的时滞细胞神经网络的指数稳定性分析  

A Generalized LMI-Based Approach to the Global Asymptotic Stability of Cellular Neural Networks with Delay

作　　者：王路平[1] 刘晓华[2] 

机构地区：[1]山东工商学院数学与信息科学学院,山东烟台264005 [2]鲁东大学数学与信息科学学院,山东烟台264025

出　　处：《河南师范大学学报（自然科学版）》2007年第2期39-41,共3页Journal of Henan Normal University(Natural Science Edition)

基　　金：山东省自然科学基金(Y2005G01)

摘　　要：研究了一类具有时滞的细胞神经网络的指数稳定性问题,利用Lyapunov Krasovskii函数,给出了系统全局指数稳定的时滞相关稳定性条件,其结果以线性矩阵不等式的形式给出,可以很容易求出系统稳定的时滞上界,并且能够达到时滞无关指数稳定性和全局渐近稳定性.数值算例说明了本文结果的优越性.The global exponential stability problem of Cellular neural networks with delays is investigated in this paper. A new stability condition is present based on Lyapunov Krasovskii method, which is dependent on the size of delays. The results＇ are given in the form of LMI, and the admitted upper bound of the delay can be obtained easily. The time delay independent results can be got, which include some results in the former literature. Finally, a numerical example is given to illustrate the effectiveness of the main results.

关 键 词：时滞细胞神经网络 线性矩阵不等式 指数稳定 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]