ROBUST EXPONENTIAL STABILITY OF UNCERTAIN FUZZY STOCHASTIC NEUTRAL NEURAL NETWORKS WITH MIXED TIME-VARYING DELAYS

被引：8
|
作者：
Li, Yajun [1 ]
Deng, Feiqi [2 ]
Xie, Fei [1 ]
Jiao, Like [1 ]
机构：
[1] Shunde Polytech, Sch Technol, Dept Elect & Informat Engn, Desheng East Rd, Shunde Dist 528300, Foshan, Peoples R China
[2] South China Univ Technol, Dept Automat Sci & Engn, 381 Wushan Rd, Guangzhou 510641, Guangdong, Peoples R China
来源：
INTERNATIONAL JOURNAL OF INNOVATIVE COMPUTING INFORMATION AND CONTROL | 2018年 / 14卷 / 02期
基金：
中国国家自然科学基金;
关键词：
Robust exponential stability; Stochastic neutral neural networks; Linear matrix inequality (LMI); Mixed time-varying delays;
D O I：
10.24507/ijicic.14.02.615
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The robust exponential stability problem for a class of uncertain fuzzy stochastic neutral neural networks systems with mixed delays is concerned about. Based on the Lyapunov functional and the stochastic stability theory, the sufficient conditions are developed in terms of linear matrix inequalities (LMIs). Examples and simulations are provided to illustrate the effectiveness and the less conservatism of the proposed method.
引用
收藏
页码：615 / 627
页数：13
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