Exponential Synchronization for Arrays of Coupled Neural Networks with Time-delay Couplings

被引：39
|
作者：
Li, Tao [1 ]
Wang, Ting [3 ]
Song, Ai-guo [2 ]
Fei, Shu-min [3 ]
机构：
[1] Henan Polytech Univ, Sch Elect Engn & Automat, Jiaozuo 454000, Henan, Peoples R China
[2] Southeast Univ, Sch Instrument Sci & Engn, Nanjing 210096, Jiangsu, Peoples R China
[3] Southeast Univ, Minist Educ, Sch Automat, Key Lab Measurement & Control CSE, Nanjing 210096, Jiangsu, Peoples R China
来源：
INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS | 2011年 / 9卷 / 01期
基金：
中国博士后科学基金; 中国国家自然科学基金;
关键词：
Coupled neural networks; exponential synchronization; LMI approach; Lyapunov-Krasovskii functional; time-varying delay; GLOBAL SYNCHRONIZATION; ROBUST SYNCHRONIZATION; STABILITY-CRITERIA; VARYING DELAY; SYSTEMS; CIRCUITS;
D O I：
10.1007/s12555-011-0124-4
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper deals with global exponential synchronization in arrays of coupled delayed neural networks with both delayed coupling and one single delayed one. Through employing Kronecker product and convex combination technique, two novel synchronization criteria are presented in terms of linear matrix inequalities (LMIs), and these conditions are dependent on the bounds of both time-delay and its derivative. Through employing Matlab LMI Toolbox and adjusting some matrix parameters in the derived results, we can realize the design and applications of the addressed systems, which shows that our methods improve and extend those reported methods. The efficiency and applicability of the proposed results can be demonstrated by three numerical examples with simulations.
引用
收藏
页码：187 / 196
页数：10
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