混合变时滞的中立型神经网络全局指数稳定性  

Global Exponential Stability for Neutral-Type Neural Networks with Hybrid Time-Varying Delays

作　　者：吴亮[1] 尹景本[1] 王军涛[1] 

机构地区：[1]河南科技学院数学系,河南新乡453003

出　　处：《河南科学》2009年第12期1493-1496,共4页Henan Science

基　　金：河南省教育厅自然科学研究项目(2007110020;2008110006)

摘　　要：利用Lyapunov-Krasovskii稳定性理论和线性矩阵不等式(LMI)处理方法,研究了一类具有混合时变时滞的中立型细胞神经网络的全局指数稳定性问题,获得了该模型平衡点全局指数稳定的一个新的充分条件.改进和推广了已有文献的结果,降低了系统的保守性.所得结论对更好的模拟细胞神经网络的行为具有重要的指导意义.Based on the Lyapunov-Krasovskii functional stability analysis and the linear matrix inequality （LMI） approach, the global exponential stability was discussed for the neutral-type cellular neural networks with discrete and distributed time-varying delays,a new sufficient condition was derived to assure the global exponential stability of the equilibrium. The criterion improved and extended the results of literature,and has less conservative. The obtained conclusion has the important theoretical and practical significance to the better simulate cellular neural networks＇ behavior.

关 键 词：离散时滞 分布时滞 中立型细胞神经网络 Lyapunov—Krasovskii方程 线性矩阵不等式(LMI) 全局指数稳定性 

分 类 号：O175[理学—数学]