CC BY 4.0 UnportedPánis, RadimAdámek, KarelMarwan, Norbert2023-02-132023-02-132022https://oa.tib.eu/renate/handle/123456789/11443http://dx.doi.org/10.34657/10477Recurrence 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).enghttps://creativecommons.org/licenses/by/4.0530noiseplotsArticle