Local Synchronization Criteria of Markovian Nonlinearly Coupled Neural Networks With Uncertain and Partially Unknown Transition Rates

被引:43
作者
Wang, Junyi [1 ]
Zhang, Huaguang [1 ,2 ]
Wang, Zhanshan [1 ]
Shan, Qihe [1 ]
机构
[1] Northeastern Univ, Coll Informat Sci & Engn, Shenyang 110819, Liaoning, Peoples R China
[2] Northeastern Univ, State Key Lab Synthet Automat Proc Ind, Shenyang 110819, Liaoning, Peoples R China
来源
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS | 2017年 / 47卷 / 08期
基金
中国国家自然科学基金; 国家高技术研究发展计划(863计划);
关键词
Free-matrix-based integral inequality; further improved integral inequality; local synchronization; uncertain and partially unknown transition rates; TIME-DELAY SYSTEMS; COMPLEX DYNAMICAL NETWORKS; STABILITY ANALYSIS; EXPONENTIAL SYNCHRONIZATION; JUMP SYSTEMS; DISTRIBUTED DELAYS; GLOBAL SYNCHRONIZATION; LINEAR-SYSTEMS; DISCRETE; PROBABILITIES;
D O I
10.1109/TSMC.2016.2582543
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 local synchronization problem of Markovian nonlinearly coupled neural networks with uncertain and partially unknown transition rates is investigated. Each transition rate in this Markovian nonlinearly coupled neural networks model is uncertain or completely unknown because the complete knowledge on the transition rates is difficult and the cost is probably high. By applying the Lyapunov-Krasovskii functional, a new integral inequality combining with free-matrix-based integral inequality and further improved integral inequality, the less conservative local synchronization criteria are obtained. The new delay-dependent local synchronization criteria containing the bounds of delay and delay derivative are given in terms of linear matrix inequalities. Finally, a simulation example is provided to illustrate the effectiveness of the proposed method.
引用
收藏
页码:1953 / 1964
页数:12
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