Title
Fast parametric time–frequency modeling of nonstationary signals
Abstract
This paper studies the approximation of nonstationary signals from natural life systems in time–frequency plane using a type of four-parameter Gabor atoms. These four parameters, i.e. the dilation, chirprate, modulation and translation, have clear physical meanings and to optimize these parameters is an extremely difficult task. In this paper, a fast procedure is introduced without explicitly exploring these parameters over the continuous search space. Here, these four parameters together with a phase parameter for real signal are assigned with random values across their full ranges, creating a large library of candidate Gabor atoms. Then a fast algorithm is used to select atoms from the library that best approximate the nonstationary signal. The computational complexity of the method is only linearly related with the library size, the number of signal points and the number of used atoms. The proposed method is applied to several benchmark problems from life systems, including the bat signals, EEG signals and speech signals. The simulation results confirm its efficacy.
Year
DOI
Venue
2008
10.1016/j.amc.2008.05.068
Applied Mathematics and Computation
Keywords
Field
DocType
Nonstationary signal,Time–frequency analysis,Chirplet
Mathematical optimization,Dilation (morphology),Algorithm,Modulation,Parametric statistics,Time–frequency analysis,Numerical analysis,Mathematics,Computational complexity theory
Journal
Volume
Issue
ISSN
205
1
0096-3003
Citations 
PageRank 
References 
2
0.40
4
Authors
2
Name
Order
Citations
PageRank
Shiwei Ma113621.79
Kang Li260779.66