Surrogate Test to Distinguish between Chaotic and Pseudoperiodic Time Series

dc.creatorLuo, Xiaodong
dc.creatorNakamura, Tomomichi
dc.creatorSmall, Michael
dc.date2004-04-29
dc.date2005-01-06
dc.date.accessioned2026-07-07T05:35:30Z
dc.date.available2026-07-07T05:35:30Z
dc.descriptionIn this communication a new algorithm is proposed to produce surrogates for pseudoperiodic time series. By imposing a few constraints on the noise components of pseudoperiodic data sets, we devise an effective method to generate surrogates. Unlike other algorithms, this method properly copes with pseudoperiodic orbits contaminated with linear colored observational noise. We will demonstrate the ability of this algorithm to distinguish chaotic orbits from pseudoperiodic orbits through simulation data sets from theRössler system. As an example of application of this algorithm, we will also employ it to investigate a human electrocardiogram (ECG) record.
dc.descriptionAccepted version, to appear in Phys. Rev. E
dc.identifierhttps://arxiv.org/abs/nlin/0404054
dc.identifierhttp://arxiv.org/abs/nlin/0404054
dc.identifierPhys. Rev. E 71, 026230 (2005)
dc.identifierdoi:10.1103/PhysRevE.71.026230
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/80716
dc.subjectChaotic Dynamics
dc.titleSurrogate Test to Distinguish between Chaotic and Pseudoperiodic Time Series
dc.typetext

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