Exponential Stability for Stochastic Neural Networks of Neutral-type with Discrete and Distributed Time-delays

被引：0
|
作者：
Zhu Qingyu [1 ]
Zhou Wuneng [1 ]
Mou Xiaozheng [1 ]
机构：
[1] Donghua Univ, Coll Informat Sci & Technol, Shanghai 201620, Peoples R China
来源：
PROCEEDINGS OF THE 29TH CHINESE CONTROL CONFERENCE | 2010年
关键词：
Exponential Stability; Neutral Neural Networks; Distributed Time-delays; Linear Matrix Inequality (LMI); GLOBAL STABILITY;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper, the global robust exponential stability is investigated for uncertain neural networks of neutral-type with mixed time delays. Based on Lyapunov-Krasovskii stability theory and stochastic analysis approaches, several new criteria and derived to guarantee the exponential stability of the system. A numerical example is given to demonstrate the applicability of our proposed stability criteria.
引用
收藏
页码：2397 / 2401
页数：5
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