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Recovering Network Structures With Time-Varying Nodal Parameters

文献类型：期刊论文

作者Wang, Xiong4,5; Lu, Jinhu1,3; Wu, Xiaoqun2
刊名IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
出版日期2020-07-01
卷号50期号:7页码:2588-2598
关键词Complex networks Time-varying systems Taylor series Power system dynamics Vehicle dynamics Topology Complex network Lasso method network reconstruction time-varying nodal parameter
ISSN号2168-2216
DOI10.1109/TSMC.2018.2822780
英文摘要Complex networks with time-varying nodal parameters are of considerable interest and significance in many areas of science and engineering. Reconstructing networks with unknown but continuously bounded time-varying nodal parameters from limited measured information is desirable and of significant interest for using and controlling these networks. Based on the Lasso method and the Taylor expansion approximation, we develop an efficient and feasible, completely data-driven approach to predicting the structures of networks with unknown but continuously bounded time-varying nodal parameters in the presence or absence of noise. In particular, the reconstruction framework is implemented on several different kinds of artificial, two-layer and real complex networks composed of various parameter-varying nodal dynamics. Through numerical simulations, we demonstrate that, networks structures can be fully reconstructed with limited available information and presence or absence of noise, though systemic parameters are continuously time-varying. In addition, our method is also applicable to structure identification of multilayer networks as well as networks with constant nodal parameters. We expect our method to be useful in addressing issues of significantly current concern in the information era, natural networks, and large-scale multilayer networks.
资助项目National Key Research and Development Program of China[2016YFB0800401] ; National Natural Science Foundation of China[61621003] ; National Natural Science Foundation of China[61532020] ; National Natural Science Foundation of China[11472290] ; National Natural Science Foundation of China[61472027] ; National Natural Science Foundation of China[61573262]
WOS研究方向Automation & Control Systems ; Computer Science
语种英语
WOS记录号WOS:000544033400025
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
源URL[http://ir.amss.ac.cn/handle/2S8OKBNM/51729]  
专题中国科学院数学与系统科学研究院
通讯作者Lu, Jinhu
作者单位1.Beihang Univ, Sch Automat Sci & Elect Engn, State Key Lab Software Dev Environm, Beijing Adv Innovat Ctr Big Data & Brain Comp, Beijing 100191, Peoples R China
2.Wuhan Univ, Sch Math & Stat, Wuhan 430072, Peoples R China
3.Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100190, Peoples R China
4.Univ Chinese Acad Sci, Sch Math Sci, Beijing 100049, Peoples R China
5.Chinese Acad Sci, Acad Math & Syst Sci, LSC, Beijing 100190, Peoples R China
推荐引用方式
GB/T 7714		 Wang, Xiong,Lu, Jinhu,Wu, Xiaoqun. Recovering Network Structures With Time-Varying Nodal Parameters[J]. IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS,2020,50(7):2588-2598.
APA Wang, Xiong,Lu, Jinhu,&Wu, Xiaoqun.(2020).Recovering Network Structures With Time-Varying Nodal Parameters.IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS,50(7),2588-2598.
MLA Wang, Xiong,et al."Recovering Network Structures With Time-Varying Nodal Parameters".IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS 50.7(2020):2588-2598.

入库方式： OAI收割

来源：数学与系统科学研究院

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