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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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Author:Deniz Eroglu, Norbert Marwan, Sushma Prasad, Jürgen KurthsORCiDGND
ISSN:1023-5809 (print)
Parent Title (English):Nonlinear processes in geophysics
Place of publication:Göttingen
Document Type:Article
Year of first Publication:2014
Year of Completion:2014
Release Date:2017/03/27
First Page:1085
Last Page:1092
Funder: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 Erd- und Umweltwissenschaften
Peer Review:Referiert
Publication Way:Open Access