DocumentCode
3018572
Title
Comparison of nonparametric and parametric time-varying methods for quantifying phase synchrony
Author
Mutlu, Ali Yener ; Aviyente, Selin
Author_Institution
Dept. of Electr. & Comput. Eng., Michigan State Univ., East Lansing, MI, USA
fYear
2010
fDate
7-10 Nov. 2010
Firstpage
1991
Lastpage
1995
Abstract
Quantifying the pairwise relationships between two signals is an important problem in many fields of science and engineering. Phase synchrony has been suggested as a powerful tool for determining bivariate signal relationships. Recently, a nonparametric phase estimation method based on the Rihaczek distribution belonging to Cohen´s class of time-frequency distributions (TFDs) has been proposed for the estimation of time-varying phase. Alternatively, parametric time-frequency methods, which model the phase as a polynomial, can be used. In this paper, the nonparametric phase estimator based on the Rihaczek distribution is compared with the parametric estimator based on the high-order ambiguity function for their accuracy in estimating phase synchrony.
Keywords
nonparametric statistics; phase estimation; polynomials; signal processing; time-varying networks; Rihaczek distribution; bivariate signal relationships; high-order ambiguity function; nonparametric phase estimator; nonparametric time-varying methods; parametric time-frequency methods; phase synchrony; time-frequency distributions; Couplings; Noise robustness; Oscillators; Phase estimation; Polynomials; Signal to noise ratio; Time frequency analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Signals, Systems and Computers (ASILOMAR), 2010 Conference Record of the Forty Fourth Asilomar Conference on
Conference_Location
Pacific Grove, CA
ISSN
1058-6393
Print_ISBN
978-1-4244-9722-5
Type
conf
DOI
10.1109/ACSSC.2010.5757889
Filename
5757889
Link To Document