Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/4794
Title: Detecting chaos in pseudoperiodic time series without embedding
Authors: Zhang, J
Luo, X
Small, M
Keywords: Acoustic noise
Chaos theory
Data acquisition
Reliability
Chaos
Encoding
Spatiotemporal phenomena
Time series
Issue Date: 24-Jan-2006
Publisher: American Physical Society
Source: Physical review E, statistical, nonlinear, and soft matter physics, Jan. 2006, v. 73, no. 1, 016216, p. 1-5 How to cite?
Journal: Physical review E, statistical, nonlinear, and soft matter physics 
Abstract: A different method is proposed to detect deterministic structure from a pseudoperiodic time series. By using the correlation coefficient as a measure of the distance between cycles, we are exempt from phase-space reconstruction and further construct a hierarchy of pseudocycle series that, in turn, preserve less determinism than the original time series. Appropriate statistics are then devised to reveal the temporal and spatial correlation encoded in this hierarchy of the pseudocycle series, which allows for a reliable detection of determinism and chaos in the original time series. We demonstrate that this method can reliably identify chaos in the presence of noise of different sources for both artificial data and experimental time series.
URI: http://hdl.handle.net/10397/4794
ISSN: 1539-3755 (print)
1550-2376 (online)
DOI: 10.1103/PhysRevE.73.016216
Rights: Physical Review E © 2006 The American Physical Society. The Journal's web site is located at http://pre.aps.org/
Appears in Collections:Journal/Magazine Article

Files in This Item:
File Description SizeFormat 
Zhang_Detecting_Chaos_Pseudoperiodic.pdf168.45 kBAdobe PDFView/Open
Access
View full-text via PolyU eLinks SFX Query
Show full item record

SCOPUSTM   
Citations

25
Last Week
0
Last month
0
Citations as of Jun 4, 2016

WEB OF SCIENCETM
Citations

24
Last Week
0
Last month
0
Citations as of Aug 25, 2016

Page view(s)

177
Last Week
0
Last month
Checked on Aug 21, 2016

Download(s)

158
Checked on Aug 21, 2016

Google ScholarTM

Check

Altmetric



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.