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Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/4828

Title: Surrogate test to distinguish between chaotic and pseudoperiodic time series
Authors: Luo, Xiaodong
Nakamura, Tomomichi
Small, Michael
Subjects: Algorithms
Computer simulation
Correlation theory
Data reduction
Spurious signal noise
Time series analysis
Issue Date: 24-Feb-2005
Publisher: American Physical Society
Citation: Physical review E, statistical, nonlinear, and soft matter physics, Feb. 2005, v. 71, no. 2, 026230, p. 1-8.
Abstract: In this paper a different 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 the Rössler system. As an example of application of this algorithm, we will also employ it to investigate a human electrocardiogram record.
Description: DOI: 10.1103/PhysRevE.71.026230
Rights: Physical Review E © 2005 The American Physical Society. The Journal's web site is located at http://pre.aps.org/
Type: Journal/Magazine Article
URI: http://hdl.handle.net/10397/4828
ISSN: 1539-3755 (print)
1550-2376 (online)
Appears in Collections:EIE Journal/Magazine Articles

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