Passivity analysis of Markov jump BAM neural networks with mode-dependent mixed time-delays via piecewise-constant transition rates

被引:9
|
作者
Zhang, He [1 ]
Ji, Huihui [2 ]
Ye, Zhiyong [2 ]
Tian Senping [3 ]
机构
[1] Baise Univ, Inst Math & Stat, Baise 533000, Guangxi, Peoples R China
[2] Chongqing Univ Technol, Inst Math & Stat, Chongqing 400054, Peoples R China
[3] S China Univ Technol, Sch Automat Sci & Engn, Guangzhou 510640, Guangdong, Peoples R China
来源
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS | 2016年 / 353卷 / 06期
基金
中国国家自然科学基金;
关键词
ALMOST-PERIODIC SOLUTION; GLOBAL EXPONENTIAL STABILITY; ASYMPTOTIC STABILITY; VARYING DELAYS; DISCRETE; EXISTENCE; SYSTEMS; STABILIZATION;
D O I
10.1016/j.jfranklin.2016.02.005
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Passivity problem is studied for Markov jump bi-directional associative memory (BAM) neural networks with both mode-dependent mixed time delays and time-varying transition rates. In this paper, we consider both discrete delay and distributed delay which are all switching based on Markov process r(t). Time varying transition rates are, respectively, discussed under the cases of known transition rates and partly unknown transition rates. The mode-dependent time-varying character of transition rates is supposed to be piecewise-constant. By utilizing LMIs technique and a class of Lyapunov functionals, a switching delay passivity criterion underlying known transition rates is derived, which can be easily checked by the Matlab LMI Tool Box. Furthermore, we extend the result to passivity analysis of Markov jump BAM neural networks with partly unknown transition rates. The results obtained relate on not only switching discrete delays but also switching distributed delays. Finally, a numerical example is given to illustrate the effectiveness of the results. (C) 2016 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码:1436 / 1459
页数:24
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