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Universal data-based method for reconstructing complex networks with binary-state dynamics

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dc.contributor.authorLi, Jingwen
dc.contributor.authorShen, Zhesi
dc.contributor.authorWang, Wen-Xu
dc.contributor.authorGrebogi, Celso
dc.contributor.authorLai, Ying-Cheng
dc.contributor.institutionUniversity of Aberdeen.Physicsen
dc.contributor.institutionUniversity of Aberdeen.Institute for Complex Systems and Mathematical Biology (ICSMB)en
dc.date.accessioned2017-01-16T12:28:41Z
dc.date.available2017-01-16T12:28:41Z
dc.date.issued2017-03-02
dc.descriptionACKNOWLEDGMENTS W.-X.W. was supported by NSFC under Grant No. 61573064, No. 61074116, and No. 71631002, as well as the Fundamental Research Funds for the Central Universities, Beijing Nova Programme. Y.-C.L. was supported by ARO under Grant No. W911NF-14-1-0504. W.-X.W. designed research; J.L. and Z.S. performed research; all analyzed data; J.L., W.-X.W., and Y.-C.L. wrote the paper; all edited the paper. The authors declare no competing financial interests.en
dc.description.statusPeer revieweden
dc.format.extent12
dc.format.extent1503574
dc.identifier59398440
dc.identifierd650294c-0292-46cc-a632-d432f0fd10d4
dc.identifier85014843412
dc.identifier.citationLi, J, Shen, Z, Wang, W-X, Grebogi, C & Lai, Y-C 2017, 'Universal data-based method for reconstructing complex networks with binary-state dynamics', Physical Review. E, Statistical, Nonlinear and Soft Matter Physics, vol. 95, no. 3, 032303, pp. 1-12. https://doi.org/10.1103/PhysRevE.95.032303en
dc.identifier.doi10.1103/PhysRevE.95.032303
dc.identifier.iss3en
dc.identifier.issn1539-3755
dc.identifier.otherArXiv: http://arxiv.org/abs/1511.06852v1
dc.identifier.otherORCID: /0000-0002-9811-4617/work/107062064
dc.identifier.urihttp://hdl.handle.net/2164/7997
dc.identifier.urlhttp://arxiv.org/abs/1511.06852v1en
dc.identifier.vol95en
dc.language.isoeng
dc.relation.ispartofPhysical Review. E, Statistical, Nonlinear and Soft Matter Physicsen
dc.subjectQC Physicsen
dc.subject.lccQCen
dc.titleUniversal data-based method for reconstructing complex networks with binary-state dynamicsen
dc.typeJournal articleen

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