Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/5385
PIRA download icon_1.1View/Download Full Text
Title: Unified framework for detecting phase synchronization in coupled time series
Authors: Sun, J
Small, M
Issue Date: Oct-2009
Source: Physical review. E, Statistical, nonlinear, and soft matter physics, Oct. 2009, v. 80, no. 4, 046219, p. 1-11
Abstract: Phase synchronization (PS) has drawn increasing attention in recent years for its extensive applications in analyzing time series observed from coupled systems. In this paper, we examine the detection of PS in bivariate time series from the viewpoints of signal processing and circular statistics. Several definitions of instantaneous phase (IP) are first revisited and further unified into a framework, which defines IP as the argument of the signal with a specific bandpass filter applied. With this framework, the constraints for IP definition are discussed and the effect of noise in IP estimation is studied. The estimate error of IP, which is due to noise, is shown to obey a scale mixture of normal (SMN) distributions. Further, under the assumption that the SMN of IP error can be approximated by a particular normal distribution, the estimate of mean phase coherence of bivariate time series is shown to be degraded by a factor, which is determined by only the level of in-band noise. Finally, simulations are provided to support the theoretical results.
Keywords: Normal distribution
Synchronisation
Time series
Publisher: American Physical Society
Journal: Physical review. E, Statistical, nonlinear, and soft matter physics 
ISSN: 1539-3755
EISSN: 1550-2376
DOI: 10.1103/PhysRevE.80.046219
Rights: Physical Review E © 2009 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 
Sun_Synchronization_Time_Series.pdf403.3 kBAdobe PDFView/Open
Open Access Information
Status open access
File Version Version of Record
Access
View full-text via PolyU eLinks SFX Query
Show full item record

Page views

69
Last Week
3
Last month
Citations as of May 22, 2022

Downloads

170
Citations as of May 22, 2022

SCOPUSTM   
Citations

31
Last Week
0
Last month
0
Citations as of May 26, 2022

WEB OF SCIENCETM
Citations

27
Last Week
0
Last month
0
Citations as of May 26, 2022

Google ScholarTM

Check

Altmetric


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