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Finding Recurrence Networks' Threshold Adaptively for a Specific Time Series : Volume 21, Issue 6 (11/11/2014)

By Eroglu, D.

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Book Id: WPLBN0003991313
Format Type: PDF Article :
File Size: Pages 8
Reproduction Date: 2015

Title: Finding Recurrence Networks' Threshold Adaptively for a Specific Time Series : Volume 21, Issue 6 (11/11/2014)  
Author: Eroglu, D.
Volume: Vol. 21, Issue 6
Language: English
Subject: Science, Nonlinear, Processes
Collections: Periodicals: Journal and Magazine Collection (Contemporary), Copernicus GmbH
Publication Date:
Publisher: Copernicus Gmbh, Göttingen, Germany
Member Page: Copernicus Publications


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Prasad, S., Kurths, J., Marwan, N., & Eroglu, D. (2014). Finding Recurrence Networks' Threshold Adaptively for a Specific Time Series : Volume 21, Issue 6 (11/11/2014). Retrieved from

Description: Potsdam Institute for Climate Impact Research, Potsdam, Germany. 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.

Finding recurrence networks' threshold adaptively for a specific time series

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