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Border effect corrections for diagonal line based recurrence quantification analysis measures

•In recurrence quantification analysis, border effects and tangential motion can bias diagonal line based characteristics.•Border effect bias can be minimized by a simple alteration of the diagonal line length histogram.•A parameter free, skeletonization method reduces artifacts due to tangential mo...

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Bibliographic Details
Published in:Physics letters. A 2019-12, Vol.383 (34), p.125977, Article 125977
Main Authors: Kraemer, K. Hauke, Marwan, Norbert
Format: Article
Language:English
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Summary:•In recurrence quantification analysis, border effects and tangential motion can bias diagonal line based characteristics.•Border effect bias can be minimized by a simple alteration of the diagonal line length histogram.•A parameter free, skeletonization method reduces artifacts due to tangential motion and leaves an RP of thin diagonal lines.•The proposed correction schemes lead to diagonal line entropies that fall within analytically derived expectation ranges. Recurrence Quantification Analysis (RQA) defines a number of quantifiers, which base upon diagonal line structures in the recurrence plot (RP). Due to the finite size of an RP, these lines can be cut by the borders of the RP and, thus, bias the length distribution of diagonal lines and, consequently, the line based RQA measures. In this letter we investigate the impact of the mentioned border effects and of the thickening of diagonal lines in an RP (caused by tangential motion) on the estimation of the diagonal line length distribution, quantified by its entropy. Although a relation to the Lyapunov spectrum is theoretically expected, the mentioned entropy yields contradictory results in many studies. Here we summarize correction schemes for both, the border effects and the tangential motion and systematically compare them to methods from the literature. We show that these corrections lead to the expected behavior of the diagonal line length entropy, in particular meaning zero values in case of a regular motion and positive values for chaotic motion. Moreover, we test these methods under noisy conditions, in order to supply practical tools for applied statistical research.
ISSN:0375-9601
1873-2429
DOI:10.1016/j.physleta.2019.125977