Robust stability criteria for uncertain stochastic neural networks of neutral-type with interval time-varying delays

被引：27
|
作者：
Liu, Guoquan [1 ]
Yang, Simon X. [1 ,2 ]
Chai, Yi [1 ]
Feng, Wei [3 ]
Fu, Wei [1 ]
机构：
[1] Chongqing Univ, Coll Automat, Chongqing 400044, Peoples R China
[2] Univ Guelph, Sch Engn, Guelph, ON N1G 2W1, Canada
[3] Chongqing Educ Coll, Dept Comp Sci, Chongqing 400067, Peoples R China
来源：
NEURAL COMPUTING & APPLICATIONS | 2013年 / 22卷 / 02期
关键词：
Robust stability; Neural networks; Neutral-type; Time-varying delays; Lyapunov-Krasovskill functional; GLOBAL EXPONENTIAL STABILITY; CONTROL-SYSTEMS; OPTIMIZATION; DISCRETE;
D O I：
10.1007/s00521-011-0696-1
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper deals with the robust stability problem of uncertain stochastic neural networks of neutral-type with interval time-varying delays. The uncertainties under consideration are norm-bounded, and the delay is assumed to be time-varying and belongs to a given interval. By using the Lyapunov-Krasovskill functional method and the linear matrix inequality (LMI) technique, the novel stability criteria are derived in terms of LMI. Finally, numerical examples are provided to demonstrate the effectiveness of the proposed criteria.
引用
收藏
页码：349 / 359
页数：11
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