Adaptive Synchronization for Neutral-Type Neural Networks with Stochastic Perturbation and Markovian Switching Parameters

被引：112
|
作者：
Zhou, Wuneng [1 ]
Zhu, Qingyu [1 ]
Shi, Peng [2 ,3 ]
Su, Hongye [4 ]
Fang, Jian'an [1 ]
Zhou, Liuwei [1 ]
机构：
[1] Donghua Univ, Sch Informat Sci & Technol, Shanghai 200051, Peoples R China
[2] Univ Adelaide, Sch Elect & Elect Engn, Adelaide, SA 5005, Australia
[3] Victoria Univ, Coll Engn & Sci, Melbourne, Vic 8001, Australia
[4] Zhejiang Univ, Inst Cyber Syst & Control, Natl Lab Ind Control Technol, Hangzhou 310027, Zhejiang, Peoples R China
来源：
IEEE TRANSACTIONS ON CYBERNETICS | 2014年 / 44卷 / 12期
基金：
上海市自然科学基金; 澳大利亚研究理事会;
关键词：
Adaptive synchronization; M-matrix; Markovian switching; neutral-type neural network; MASTER-SLAVE SYSTEMS; TIME-VARYING DELAYS; LAG SYNCHRONIZATION; DISTRIBUTED DELAYS; DISCRETE; STABILITY;
D O I：
10.1109/TCYB.2014.2317236
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper, the problem of adaptive synchronization is investigated for stochastic neural networks of neutral-type with Markovian switching parameters. Using the M-matrix approach and the stochastic analysis method, some sufficient conditions are obtained to ensure three kinds of adaptive synchronization for the stochastic neutral-type neural networks. These three kinds of adaptive synchronization include the almost sure asymptotical synchronization, exponential synchronization in pth moment and almost sure exponential synchronization. Some numerical examples are provided to illustrate the effectiveness and potential of the proposed design techniques.
引用
收藏
页码：2848 / 2860
页数：13
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