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Finding Recurrence Networks' Threshold Adaptively for a Specific Time Series : Volume 1, Issue 1 (24/04/2014)

By Eroglu, D.

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Book Id: WPLBN0004020107
Format Type: PDF Article :
File Size: Pages 20
Reproduction Date: 2015

Title: Finding Recurrence Networks' Threshold Adaptively for a Specific Time Series : Volume 1, Issue 1 (24/04/2014)  
Author: Eroglu, D.
Volume: Vol. 1, Issue 1
Language: English
Subject: Science, Nonlinear, Processes
Collections: Periodicals: Journal and Magazine Collection, 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 1, Issue 1 (24/04/2014). Retrieved from

Description: Potsdam Institute for Climate Impact Research, Potsdam, Germany. Recurrence plot based recurrence networks are an approach to analyze time series using 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 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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