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

页码：2397 / 2401

页数：5

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