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Journal Article

Averaged recurrence quantification analysis


Pánis,  Radim
Potsdam Institute for Climate Impact Research;

Adámek,  Karel
External Organizations;


Marwan,  Norbert
Potsdam Institute for Climate Impact Research;

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Pánis, R., Adámek, K., Marwan, N. (2023): Averaged recurrence quantification analysis. - European Physical Journal - Special Topics, 232, 1, 47-56.

Cite as: https://publications.pik-potsdam.de/pubman/item/item_27986
Recurrence quantification analysis (RQA) is a well established method of nonlinear data analysis. In this work, we present a new strategy for an almost parameter-free RQA. The approach finally omits the choice of the threshold parameter by calculating the RQA measures for a range of thresholds (in fact recurrence rates). Specifically, we test the ability of the RQA measure determinism, to sort data with respect to their signal to noise ratios. We consider a periodic signal, simple chaotic logistic equation, and Lorenz system in the tested data set with different and even very small signal-to-noise ratios of lengths 102,103,104, and 105. To make the calculations possible, a new effective algorithm was developed for streamlining of the numerical operations on graphics processing unit (GPU).