Averaged recurrence quantification analysis Method omitting the recurrence threshold choice

@article{65861,
   author = {Pánis, Radim and Adámek, Karel and Marwan, Norbert},
   article_number = {October},
   doi = {http://dx.doi.org/10.1140/epjs/s11734-022-00686-4},
   keywords = {Recurrence quantification analysis ;noise},
   language = {eng},
   issn = {1951-6355},
   journal = {EUROPEAN PHYSICAL JOURNAL-SPECIAL TOPICS},
   title = {Averaged recurrence quantification analysis Method omitting the recurrence threshold choice},
   url = {https://link.springer.com/article/10.1140/epjs/s11734-022-00686-4},
   volume = {2022},
   year = {2022}
}

TY  - JOUR
ID  - 65861
AU  - Pánis, Radim - Adámek, Karel - Marwan, Norbert
PY  - 2022
TI  - Averaged recurrence quantification analysis Method omitting the recurrence threshold choice
JF  - EUROPEAN PHYSICAL JOURNAL-SPECIAL TOPICS
VL  - 2022
IS  - October
SP  - 1-10
EP  - 1-10
SN  - 19516355
KW  - Recurrence quantification analysis ;noise
UR  - https://link.springer.com/article/10.1140/epjs/s11734-022-00686-4
N2  - 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).
ER  - 

PÁNIS, Radim, Karel ADÁMEK a Norbert MARWAN. Averaged recurrence quantification analysis Method omitting the recurrence threshold choice. \textit{EUROPEAN PHYSICAL JOURNAL-SPECIAL TOPICS}. 2022, roč.~2022, October, s.~1-10. ISSN~1951-6355. Dostupné z: https://dx.doi.org/10.1140/epjs/s11734-022-00686-4.