基于LMI方法的多时滞随机神经网络的指数稳定性

数学物理学报 ›› 2010, Vol. 30 ›› Issue (1): 42-53.

基于LMI方法的多时滞随机神经网络的指数稳定性

汪红初, 胡适耕

华南师范大学数学科学学院广州 510631

收稿日期:2007-11-08 修回日期:2009-05-31 出版日期:2010-01-01 发布日期:2010-01-01
基金资助:
国家自然科学基金(10826095, 10801056)资助

Exponential Stability for Stochastic Neural Networks with Multiple Delays: an LMI Approach

WANG Hong-Chu, HU Shi-Geng

School of Mathematical Sciences, South China Normal University, Guangzhou 510631

Received:2007-11-08 Revised:2009-05-31 Online:2010-01-01 Published:2010-01-01
Supported by:
国家自然科学基金(10826095, 10801056)资助

摘要/Abstract

摘要：

研究了一类具有多个时滞的随机神经网络的均方指数稳定性问题, 应用Lyapunov-Krasovskii泛函稳定理论和线性矩阵不等式(LMI)方法, 建立了该系统解的指数稳定判别准则, 最后通过数值举例阐述了结果的有效性.

关键词: 指数稳定, 线性矩阵不等式, Lyapunov-Krasovskii泛函, 随机神经网络.

Abstract:

This paper studies mean square exponential stability for a class of stochastic neural networks with multiple constant or time-varying delays. Based on the Lyapunov-Krasovskii stability theory, new stability criterion is derived in terms of the linear matrix inequalities (LMIs) for these networks. Some examples are also presented as illustration.

Key words: Exponential stability, Linear matrix inequality (LMI), Multiple delays, Lyapunov-Krasovskii functional, Stochastic neural networks

中图分类号:

60H10

汪红初, 胡适耕. 基于LMI方法的多时滞随机神经网络的指数稳定性[J]. 数学物理学报, 2010, 30(1): 42-53.

WANG Hong-Chu, HU Shi-Geng. Exponential Stability for Stochastic Neural Networks with Multiple Delays: an LMI Approach[J]. Acta mathematica scientia,Series A, 2010, 30(1): 42-53.

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