Mean square exponential stability of stochastic high-order Hopfield neural networks with time-varying delays

被引：0
|
作者：
Shi, Xiangdong [1 ]
机构：
[1] Wuzhou Univ, Sch Math & Phys, Wuzhou 543002, Peoples R China
来源：
SENSORS, MEASUREMENT AND INTELLIGENT MATERIALS, PTS 1-4 | 2013年 / 303-306卷
关键词：
Stochastic delay; High-order Hopfield neural networks; Mean square exponential stability; Linear matrix inequality; Lyapunov functional; time-varying delays;
D O I：
10.4028/www.scientific.net/AMM.303-306.1532
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
In the paper, by employing the linear matrix inequality(LMI) and the Lyapunov functional methods, we present some new criteria ensuring globally mean square exponential stability. The results are applicable to all continuous non-monotonic neuron activation functions.
引用
收藏
页码：1532 / 1535
页数：4
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