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Improved Delay-dependent Robust Stability Analysis for Neutral-type Uncertain Neural Networks with Markovian jumping Parameters and Time-varying Delays

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WOS被引频次:22
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成果类型:
期刊论文
作者:
Xia, Jianwei;Park, Ju H.*;Zeng, Hongbing
通讯作者:
Park, Ju H.
作者机构:
[Park, Ju H.; Xia, Jianwei] Department of Electrical Engineering, Yeungnam University, 214-1 Dae-Dong, Kyongsan, Korea, Republic of
[Xia, Jianwei] School of Mathematics Science, Liaocheng University, Shandong, China
[Zeng, Hongbing] School of Electrical and Information Engineering, Hunan University of Technology, Zhuzhou, China
通讯机构:
[Park, Ju H.] Yeungnam Univ, Dept Elect Engn, 214-1 Dae Dong, Kyongsan 712749, South Korea.
语种:
英文
关键词:
Neutral-type neural networks;Stochastic stability;Markovian jumping parameters;Time-varying delays;LMIs
期刊:
Neurocomputing
ISSN:
0925-2312
年:
2015
卷:
149
期:
PC
页码:
1198-1205
文献类别:
WOS:Article;EI:Journal article (JA)
所属学科:
ESI学科类别:计算机科学;WOS学科类别:Computer Science, Artificial Intelligence
入藏号:
WOS:000356105100007;EI:20144900276319
基金类别:
National Natural Science Foundation of China [61004046, 61104117]; National Research Foundation of Korea (NRF) - Ministry of Education, Science and Technology [2013R1A1A2A 10005201]
机构署名:
本校为其他机构
院系归属:
电气与信息工程学院
摘要:
This paper deals with the problem of robust stochastic stability analysis for a class of neutral-type uncertain neural networks with Markovian jumping parameters and time-varying delays. By introducing an novel mode-dependent Augmented Lyapunov-Krasovskii functional with delay partitioning and Wirtinger-based integral inequality techniques, some improved delay-dependent stochastically stable conditions are proposed in the form of LMIs. Numerical simulations are provided to show the effectiveness and less conservatism of the results.
参考文献:
Xia JW, 2012, J FRANKLIN I, V349, P741, DOI 10.1016/j.jfranklin.2011.09.009
Chen WM, 2013, NEUROCOMPUTING, V120, P569, DOI 10.1016/j.neucom.2013.04.013
Zhang D, 2014, NEUROCOMPUTING, V139, P321, DOI 10.1016/j.neucom.2014.02.025
Xia JW, 2014, NEUROCOMPUTING, V140, P210, DOI 10.1016/j.neucom.2014.03.022
Ma Q, 2011, NEUROCOMPUTING, V74, P2157, DOI 10.1016/j.neucom.2011.01.016

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