常时滞细胞神经网络稳定性分析  

Stability Analysis for Cellular Neural Networks with Constant Time Delay

作　　者：丁明智[1] 虞继敏[2,3] 

机构地区：[1]广西师范学院数学科学学院,广西南宁530023 [2]重庆邮电大学数理学院,重庆400065 [3]教育部直属神经网络控制和智能仪器重点实验室(重庆邮电大学),重庆400065

出　　处：《广西师范学院学报（自然科学版）》2010年第1期26-32,共7页Journal of Guangxi Teachers Education University(Natural Science Edition)

基　　金：广西教育厅科研处面上项目(200707ms063);重庆市自然科学基金(CSTC;2009BB3280)

摘　　要：该文研究了一类常时滞细胞神经网络的稳定性.构造Lyapunov-Krasovskii函数和线性矩阵不等式(LMI)对此类问题进行了探讨,并得出稳定性判据.所得判据提供了一些参数来适当地弥补了反馈矩阵与时滞反馈矩阵之间的平衡关系.而且所得的判据与时滞无关,推广了以前文献中出现的结果且具有更少的限制.数值仿真说明了该文所介绍的方法的有效性.This paper deals with the problem of stabilization for a class of cellular Neural Networks with constant time delay. A new stability criterion is derived by utilizing the Lyapunove-Krasovskii func- tional method and the matrix inequality approach. The condition provides some parameters to appropriately compensate for the tradeoff between the matrix definite condition on feedback matrix and delayed feedback matrix. This criterion is less restrictive, and generalizes some of the previous stability results derived in the literature. Numerical simulation result illutrates the effectiveness of the method proposed in this paper.

关 键 词：时滞细胞神经网络 线性矩阵不等式(LMI) Lyapunov—Krasovskii函数 

分 类 号：O231.2[理学—运筹学与控制论]