EXPONENTIAL STABILITY OF STOCHASTIC INTERVAL CELLULAR NEURAL NETWORKS WITH DELAYS

被引：0
|
作者：
Han, Jin-Fang [1 ]
Li, Fa-Chao [2 ]
机构：
[1] Hebei Univ Sci & Technol, Inst Engn Math, Shijiazhuang 050018, Peoples R China
[2] Hebei Univ Sci & Technol, Coll Econ & Management, Shijiazhuang, Peoples R China
来源：
PROCEEDINGS OF 2009 INTERNATIONAL CONFERENCE ON WAVELET ANALYSIS AND PATTERN RECOGNITION | 2009年
基金：
中国国家自然科学基金;
关键词：
Stochastic Cellular Neural Networks; Exponential Stability; Lyapunov function; Ito formula; Delays; ROBUST STABILITY; TIME DELAYS; SYSTEMS;
D O I：
10.1109/ICWAPR.2009.5207427
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
In this paper, the exponential stability problem of a class of stochastic interval delayed cellular neural networks is studied. Firstly, a kind of equivalent description of this stochastic interval delayed cellular neural networks is presented. Then by using the Ito formula, Razumikhin theorems, Lyapunov function and norm inequalities, several simple sufficient conditions are obtained which guarantee the exponential stability of the stochastic interval cellular neural networks. and some recent results reported in the literature are generalized.
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页码：175 / +
页数：2
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