Synchronization Control for Stochastic Neural Networks with Mixed Time-Varying Delays

被引：2
|
作者：
Zhu, Qing [1 ,2 ]
Song, Aiguo [1 ]
Fei, Shumin [3 ]
Yang, Yuequan [2 ]
Cao, Zhiqiang [4 ]
机构：
[1] Southeast Univ, Sch Instrument Sci, Nanjing 210096, Jiangsu, Peoples R China
[2] Yangzhou Univ, Coll Informat Engn, Yangzhou 225009, Peoples R China
[3] Southeast Univ, Sch Automat, Nanjing 210096, Jiangsu, Peoples R China
[4] Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China
来源：
SCIENTIFIC WORLD JOURNAL | 2014年
基金：
中国国家自然科学基金;
关键词：
MARKOVIAN JUMP SYSTEMS; ADAPTIVE SYNCHRONIZATION; EXPONENTIAL STABILITY; DIRECTED NETWORKS; PARAMETERS; CONSENSUS; NODES;
D O I：
10.1155/2014/840185
中图分类号：
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号：
07 ; 0710 ; 09 ;
摘要：
Synchronization control of stochastic neural networks with time-varying discrete and continuous delays has been investigated. A novel control scheme is proposed using the Lyapunov functional method and linear matrix inequality (LMI) approach. Sufficient conditions have been derived to ensure the global asymptotical mean-square stability for the error system, and thus the drive system synchronizes with the response system. Also, the control gain matrix can be obtained. With these effective methods, synchronization can be achieved. Simulation results are presented to show the effectiveness of the theoretical results.
引用
收藏
页数：10
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