CSpace  > 系统科学研究所
Robust Reconstruction of Continuously Time-Varying Topologies of Weighted Networks
Liu, Juan1,2; Mei, Guofeng3; Wu, Xiaoqun3,4; Lu, Jinhu1,5,6,7
2018-09-01
Source PublicationIEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS
ISSN1549-8328
Volume65Issue:9Pages:2970-2982
AbstractMethodological 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.
KeywordTime-varying and state-dependent network topology structure reconstruction Taylor expansion alternating direction method of multipliers (ADMM)
DOI10.1109/TCSI.2018.2808233
Language英语
Funding ProjectNational 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 Research AreaEngineering
WOS SubjectEngineering, Electrical & Electronic
WOS IDWOS:000440852500029
PublisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Citation statistics
Cited Times:3[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.amss.ac.cn/handle/2S8OKBNM/30843
Collection系统科学研究所
Affiliation1.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
Recommended Citation
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.
Files in This Item:
There are no files associated with this item.
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Liu, Juan]'s Articles
[Mei, Guofeng]'s Articles
[Wu, Xiaoqun]'s Articles
Baidu academic
Similar articles in Baidu academic
[Liu, Juan]'s Articles
[Mei, Guofeng]'s Articles
[Wu, Xiaoqun]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Liu, Juan]'s Articles
[Mei, Guofeng]'s Articles
[Wu, Xiaoqun]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.