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Finding recurrence networks' threshold adaptively for a specific time series

  • Recurrence-plot-based recurrence networks are an approach used to analyze time series using a complex networks theory. In both approaches - recurrence plots and recurrence networks -, a threshold to identify recurrent states is required. The selection of the threshold is important in order to avoid bias of the recurrence network results. In this paper, we propose a novel method to choose a recurrence threshold adaptively. We show a comparison between the constant threshold and adaptive threshold cases to study period-chaos and even period-period transitions in the dynamics of a prototypical model system. This novel method is then used to identify climate transitions from a lake sediment record.

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Metadaten
Author details:Deniz Eroglu, Norbert MarwanORCiDGND, Sushma PrasadORCiD, Jürgen KurthsORCiDGND
DOI:https://doi.org/10.5194/npg-21-1085-2014
ISSN:1023-5809
Title of parent work (English):Nonlinear processes in geophysics
Publisher:Copernicus
Place of publishing:Göttingen
Publication type:Article
Language:English
Year of first publication:2014
Publication year:2014
Release date:2017/03/27
Volume:21
Issue:6
Number of pages:8
First page:1085
Last Page:1092
Funding institution:project "Gradual environmental change versus single catastrophe - Identifying drivers of mammalian evolution" - Leibniz Association (WGL) [SAW-2013-IZW-2]
Organizational units:Mathematisch-Naturwissenschaftliche Fakultät / Institut für Geowissenschaften
Peer review:Referiert
Publishing method:Open Access
Institution name at the time of the publication:Mathematisch-Naturwissenschaftliche Fakultät / Institut für Erd- und Umweltwissenschaften
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