PÁNIS, Radim, Karel ADÁMEK and Norbert MARWAN. Averaged recurrence quantification analysis Method omitting the recurrence threshold choice. EUROPEAN PHYSICAL JOURNAL-SPECIAL TOPICS. 2022, vol. 2022, October, p. 1-10. ISSN 1951-6355. Available from: https://dx.doi.org/10.1140/epjs/s11734-022-00686-4.
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Basic information
Original name Averaged recurrence quantification analysis Method omitting the recurrence threshold choice
Authors PÁNIS, Radim, Karel ADÁMEK and Norbert MARWAN.
Edition EUROPEAN PHYSICAL JOURNAL-SPECIAL TOPICS, 2022, 1951-6355.
Other information
Original language English
Type of outcome Article in a journal
Country of publisher Germany
Confidentiality degree is not subject to a state or trade secret
WWW URL
Organization unit Institute of physics in Opava
Doi http://dx.doi.org/10.1140/epjs/s11734-022-00686-4
UT WoS 000870928800003
Keywords in English Recurrence quantification analysis ;noise
Tags FÚ, SGS-26-2022
Tags International impact, Reviewed
Links EF18_053/0017871, research and development project.
Changed by Changed by: Mgr. Pavlína Jalůvková, učo 25213. Changed: 7/2/2023 14:55.
Abstract
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 10(2), 10(3), 10(4), and 10(5). To make the calculations possible, a new effective algorithm was developed for streamlining of the numerical operations on graphics processing unit (GPU).
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