Influence of observational noise on the recurrence quantification analysis

Anno: 2002

Autori: Thiel M., Romano M.C., Kurths J., Meucci R., Allaria E., Arecchi F.T.

Affiliazione autori: Nonlinear Dynamics, University of Potsdam, Am Neuen Palais 10, 14469 Potsdam, Germany;
Istituto Nazionale di Ottica Applicata, Largo E. Fermi 6, 50125 Firenze, Italy

Abstract: In this paper, we estimate the errors due to observational noise on the recurrence quantification analysis (RQA). Based on this estimation, we present ways to minimize these errors. We give a criterion to choose the threshold – needed for the optimal computation of the recurrence plot (RP). One important point is to show the limits of interpretability of the results of the RQA if it is applied to measured time series. We show that even though the RQA is very susceptible to observational noise, it can yield reliable results for an optimal choice of E if the noise level is not too high. We apply the results to typical models, such as white noise, the logistic map and the Lorenz system, and to experimental laser data. (C) 2002 Elsevier Science B.V. All rights reserved.

Giornale/Rivista: PHYSICA D-NONLINEAR PHENOMENA

Volume: 171 (3)      Da Pagina: 138  A: 152

Maggiori informazioni: We thank Udo Schwarz, Norbert Marwan and Kai-Uwe Thiel, for fruitful discussions. The project was supported by the DFG-Schwerpunktprogramm 1114, the DFG-Projekt: KU 837/11-1, the DFG Research Group Conflicting Rules in Cognitive Systems and the EU HPRN-CT-2000-00158.
Parole chiavi: Dynamical processes; Observational noise; Recurrence plots; Recurrence quantification analysis; Stochastic processes; Computational methods; Error analysis; Mathematical models; Random processes, Recurrence quantification analysis (RQA), White noise
DOI: 10.1016/S0167-2789(02)00586-9

Citazioni: 177
dati da “WEB OF SCIENCE” (of Thomson Reuters) aggiornati al: 2024-04-28
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