Distributed mode-dependent state estimation for semi-Markovian jumping neural networks via sampled data

doi:10.1080/00207721.2018.1552771

CASIA OpenIR > 多模态人工智能系统全国重点实验室 > 机器人理论与应用

	Distributed mode-dependent state estimation for semi-Markovian jumping neural networks via sampled data
	Ma, Chao 1,2; Wu, Wei2 ; Li, Yinlin2
发表期刊	INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE
ISSN	0020-7721
	2019
卷号	50 期号:1 页码:216-230
通讯作者	Ma, Chao(cma@ustb.edu.cn)
摘要	In this paper, a novel distributed state estimation scheme with sampled data is proposed for the semi-Markovian jumping neural networks (SMJNNs) with time-varying delays. In particular, mode-dependent distributed state estimators are designed to provide more flexibility. Based on the mode-dependent Lyapunov-Krasovskii functional, sufficient criteria are presented for ensuring the existence of the state estimators, based on which the desired mode-dependent estimator gains are further obtained. Finally, an illustrative example is presented for verifying the effectiveness and applicability of our theoretical results.
关键词	Distributed state estimation semi-Markovian jumping neural networks sampled data
DOI	10.1080/00207721.2018.1552771
关键词[WOS]	TIME-DELAY SYSTEMS ; H-INFINITY ; STABILITY ANALYSIS ; SYNCHRONIZATION ; INEQUALITY
收录类别	SCI
语种	英语
资助项目	National Natural Science Foundation of China[61703038] ; National Natural Science Foundation of China[61627808] ; National Natural Science Foundation of China[31200829] ; Fundamental Research Funds for the Central Universities[FRF-TP-15-115A1] ; National Natural Science Foundation of China[61703038] ; National Natural Science Foundation of China[61627808] ; National Natural Science Foundation of China[31200829] ; Fundamental Research Funds for the Central Universities[FRF-TP-15-115A1]
项目资助者	National Natural Science Foundation of China ; Fundamental Research Funds for the Central Universities
WOS研究方向	Automation & Control Systems ; Computer Science ; Operations Research & Management Science
WOS类目	Automation & Control Systems ; Computer Science, Theory & Methods ; Operations Research & Management Science
WOS记录号	WOS:000457606600018
出版者	TAYLOR & FRANCIS LTD
七大方向——子方向分类	智能控制
引用统计	被引频次：10[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/25286
专题	多模态人工智能系统全国重点实验室_机器人理论与应用
通讯作者	Ma, Chao
作者单位	1.Univ Sci & Technol Beijing, Sch Automat & Elect Engn, Beijing 100083, Peoples R China 2.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
第一作者单位	中国科学院自动化研究所
通讯作者单位	中国科学院自动化研究所
推荐引用方式 GB/T 7714	Ma, Chao,Wu, Wei,Li, Yinlin. Distributed mode-dependent state estimation for semi-Markovian jumping neural networks via sampled data[J]. INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE,2019,50(1):216-230.
APA	Ma, Chao,Wu, Wei,&Li, Yinlin.(2019).Distributed mode-dependent state estimation for semi-Markovian jumping neural networks via sampled data.INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE,50(1),216-230.
MLA	Ma, Chao,et al."Distributed mode-dependent state estimation for semi-Markovian jumping neural networks via sampled data".INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE 50.1(2019):216-230.