Robust Reconstruction of Continuously Time-Varying Topologies of Weighted Networks

doi:10.1109/TCSI.2018.2808233

CORC > 数学与系统科学研究院 > 中国科学院数学与系统科学研究院 > 系统科学研究所

	Robust Reconstruction of Continuously Time-Varying Topologies of Weighted Networks
	Liu, Juan 1,2; Mei, Guofeng 3; Wu, Xiaoqun 3,4; Lu, Jinhu1,5,6,7
刊名	IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS
	2018-09-01
卷号	65 期号:9 页码:2970-2982
关键词	Time-varying and state-dependent network topology structure reconstruction Taylor expansion alternating direction method of multipliers (ADMM)
ISSN号	1549-8328
DOI	10.1109/TCSI.2018.2808233
英文摘要	Methodological advance in reconstructing the structure of a complex dynamical network have enabled increasingly intricate comprehension of its evolutionary mechanisms and functional behaviors. However, we are often involved in such a situation that only a limited number of observations can be collected and the network structures are completely unknown and continuously time-varying and state-dependent. Few studies have been involved in reconstructing the continuously varying topologies of networks in time intervals via limited discrete observations. We develop a new way to reconstruct the structures of continuously time-varying and state-dependent networks by reconstructing the Taylor expansion coefficients of couplings. The alternating direction method of multipliers algorithm is applied to solve the reconstruction problem by integrating each component's information of a high-dimensional node. The robustness analysis of our method shows that the structure reconstruction under noisy observations and outliers approximates the one under accurate observations as nodal dimension increases. Different from the existing works, the advantage of our method lies in two aspects. First, the ability to reconstruct network structures via one-time dynamical evolution. Second, instead of reconstructing structures at discrete time points, we obtain the continuously varying structures in continuous time intervals. Numerical simulations are provided to illustrate the feasibility, effectiveness, and robustness of the reconstruction scheme.
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[61573262]
WOS研究方向	Engineering
语种	英语
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
WOS记录号	WOS:000440852500029
内容类型	期刊论文
源URL	[http://ir.amss.ac.cn/handle/2S8OKBNM/30842]
专题	系统科学研究所
通讯作者	Lu, Jinhu
作者单位	1.Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Sch Math Sci, Beijing 100049, Peoples R China 3.Wuhan Univ, Sch Math & Stat, Wuhan 430072, Hubei, Peoples R China 4.Wuhan Univ, Hubei Key Lab Computat Sci, Wuhan 430072, Hubei, Peoples R China 5.Beihang Univ, Sch Automat Sci & Elect Engn, State Key Lab Software Dev Environm, Beijing 100083, Peoples R China 6.Beihang Univ, Beijing Adv Innovat Ctr Big Data & Brain Machine, Beijing 100083, Peoples R China 7.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
推荐引用方式 GB/T 7714	Liu, Juan,Mei, Guofeng,Wu, Xiaoqun,et al. Robust Reconstruction of Continuously Time-Varying Topologies of Weighted Networks[J]. IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS,2018,65(9):2970-2982.
APA	Liu, Juan,Mei, Guofeng,Wu, Xiaoqun,&Lu, Jinhu.(2018).Robust Reconstruction of Continuously Time-Varying Topologies of Weighted Networks.IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS,65(9),2970-2982.
MLA	Liu, Juan,et al."Robust Reconstruction of Continuously Time-Varying Topologies of Weighted Networks".IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS 65.9(2018):2970-2982.