S-分布时滞随机区间细胞神经网络的全局指数鲁棒稳定性

J4 ›› 2012, Vol. 47 ›› Issue (3): 87-92.

S-分布时滞随机区间细胞神经网络的全局指数鲁棒稳定性

张伟伟¹,王林山^2*

1. 中国海洋大学信息科学与工程学院, 山东青岛 266100;
2. 中国海洋大学数学科学学院, 山东青岛 266100

收稿日期:2011-02-27 出版日期:2012-03-20 发布日期:2012-04-01
通讯作者: 王林山(1956- ),男,教授,博士生导师,研究方向为动力系统与神经网络.Email:WangLS@ouc.edu.cn
作者简介:张伟伟(1986- ),女,博士研究生,研究方向为动力系统与神经网络.Email:zhangww8@163.com
基金资助:
国家自然科学基金资助项目(11171374); 山东省自然科学基金重点资助项目(ZR2011AZ001)

Global exponential robust stability of stochastic interval cellularneural networks with S-type distributed delays

ZHANG Wei-wei¹, WANG Lin-shan²*

1. College of Information Science and Engineering, Ocean University of China, Qingdao 266100, Shandong, China;
2. College of Mathematical Science, Ocean University of China, Qingdao 266100, Shandong, China

Received:2011-02-27 Online:2012-03-20 Published:2012-04-01

摘要/Abstract

摘要：

利用Lyapunov稳定性理论和随机分析的方法,给出了在均方意义下系统全局指数鲁棒稳定性的判据,并且给出了几乎必然指数稳定性的代数判据,通过仿真例子说明结果的实用性。

关键词: 区间细胞神经网络;随机分析;S-分布时滞;全局指数鲁棒稳定;Lyapunov

Abstract:

By applying the Lyapunov stability theory and stochastic analysis approaches, some algebraic criteria are derived to ensure the globally robustly stochastically exponentially stability in the mean square for the addressed system, and the almost sure exponential stability is also studied. An example is given to illustrate the effectiveness and improvement over existing results.

Key words: interval cellular neural networks; stochastic analysis; S-type distributed delays; global exponential robust stability; Lyapunov

张伟伟1,王林山2*. S-分布时滞随机区间细胞神经网络的全局指数鲁棒稳定性[J]. J4, 2012, 47(3): 87-92.

ZHANG Wei-wei1, WANG Lin-shan2*. Global exponential robust stability of stochastic interval cellularneural networks with S-type distributed delays[J]. J4, 2012, 47(3): 87-92.

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