On Robust Stability for Stochastic Neural Networks of Neutral-Type with Uncertainties and Time-Varying Delays

被引：0
|
作者：
Liu, Guoquan [1 ]
Yang, Simon X. [1 ]
机构：
[1] Chongqing Univ, Coll Automat, Chongqing 630044, Peoples R China
来源：
ADVANCED MATERIALS AND ENGINEERING MATERIALS, PTS 1 AND 2 | 2012年 / 457-458卷
关键词：
Robust stability; stochastic neural networks; Neutral-type; Lyapunov-Krasovskii functional; Time-varying delays; EXPONENTIAL STABILITY; CRITERIA;
D O I：
10.4028/www.scientific.net/AMR.457-458.716
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
This paper is concerned with the robust stability analysis problem for stochastic neural networks of neutral-type with uncertainties and time-varying delays. Novel stability criteria are proposed in terms of linear matrix inequality (LM1) by defining a Lyapunov-Krasovskii functional and using the stochastic analysis technique. Two examples are given to show the effectiveness of the obtained conditions.
引用
收藏
页码：716 / 722
页数：7
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