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dc.contributor.authorZou, Yong
dc.contributor.authorDonner, Reik V.
dc.contributor.authorKurths, Juergen
dc.date.accessioned2015-05-15T15:10:03Z
dc.date.available2015-05-15T15:10:03Z
dc.date.issued2015-02-27
dc.identifier.citationZou , Y , Donner , R V & Kurths , J 2015 , ' Analyzing long-term correlated stochastic processes by means of recurrence networks : Potentials and pitfalls ' , Physical Review. E, Statistical, Nonlinear and Soft Matter Physics , vol. 91 , no. 2 , 022926 . https://doi.org/10.1103/PhysRevE.91.022926en
dc.identifier.issn1539-3755
dc.identifier.otherPURE: 46089248
dc.identifier.otherPURE UUID: 5fe0195a-20a0-42d8-b207-557b1afa3e80
dc.identifier.otherArXiv: http://arxiv.org/abs/1409.3613v1
dc.identifier.otherWOS: 000350323200011
dc.identifier.otherScopus: 84924368853
dc.identifier.urihttp://hdl.handle.net/2164/4545
dc.descriptionACKNOWLEDGMENTS Y.Z. acknowledges financial support by the NNSF of China (Grants No. 11305062, No. 11135001, and No. 81471651), the Specialized Research Fund (SRF) for the Doctoral Program (Grant No. 20130076120003), the SRF for ROCS, SEM, the Open Project Program of State Key Laboratory of Theoretical Physics, Institute of Theoretical Physics, Chinese Academy of Sciences, China (Grant No.Y4KF151CJ1), and the German Academic Exchange Service (DAAD). R.V.D. has been funded by the German Federal Ministry for Education and Research (BMBF) via the Young Investigator’s group CoSy-CC2 (Project No. 01LN1306A). The authors thank the anonymous reviewers for helpful remarks on the original version of this manuscript.en
dc.format.extent8
dc.language.isoeng
dc.relation.ispartofPhysical Review. E, Statistical, Nonlinear and Soft Matter Physicsen
dc.rights©2015 American Physical Societyen
dc.subjectdetrended fluctuation analysisen
dc.subjecttime-seriesen
dc.subjectstrange attractorsen
dc.subjectsystemsen
dc.subjecttransitionsen
dc.subjectpersistenceen
dc.subjectdimensionen
dc.subjectevolutionen
dc.subjectplotsen
dc.subjectQC Physicsen
dc.subject.lccQCen
dc.titleAnalyzing long-term correlated stochastic processes by means of recurrence networks : Potentials and pitfallsen
dc.typeJournal articleen
dc.contributor.institutionUniversity of Aberdeen.Physicsen
dc.contributor.institutionUniversity of Aberdeen.Institute for Complex Systems and Mathematical Biology (ICSMB)en
dc.description.statusPeer revieweden
dc.description.versionPreprinten
dc.identifier.doihttps://doi.org/10.1103/PhysRevE.91.022926


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