Adaptive synchronization for stochastic competitive neural networks with mixed time-varying delays

被引:43
|
作者
Gan, Qintao [1 ]
Hu, Renxi [1 ]
Liang, Yuhua [1 ]
机构
[1] Shijiazhuang Mech Engn Coll, Dept Basic Sci, Shijiazhuang 050003, Peoples R China
基金
中国国家自然科学基金;
关键词
Exponential synchronization; Stochastic competitive neural networks; Mixed time-varying delays; Adaptive control; p-Norm; GLOBAL EXPONENTIAL STABILITY; NEUTRAL-TYPE; LAG SYNCHRONIZATION; STATE ESTIMATION; SCALES; DISCRETE; PERTURBATIONS; STABILIZATION;
D O I
10.1016/j.cnsns.2012.01.021
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
This paper deals with the synchronization problem for competitive neural networks with different time scales, as well as mixed time-varying delays (both discrete and distributed time-varying delays) and stochastic disturbance. By using stochastic analysis approaches and constructing a novel Lyapunov-Krasovskii functional, an adaptive feedback controller is proposed to guarantee the exponential synchronization of proposed competitive neural networks in terms of p-norm. The synchronization results presented in this paper generalize and improve many known results. This paper also presents an illustrative example and uses simulated results of this example to show the feasibility and effectiveness of the theoretical results. (C) 2012 Elsevier B.V. All rights reserved.
引用
收藏
页码:3708 / 3718
页数:11
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