Open AccessTime–frequency analysis method based on affine Fourier transform and Gabor transform
Author(s) -
Wei Deyun,
Li YuanMin,
Wang Ruikui
Publication year - 2017
Publication title -
iet signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.384
H-Index - 42
ISSN - 1751-9683
DOI - 10.1049/iet-spr.2016.0231
Subject(s) - gabor transform , affine transformation , short time fourier transform , fourier transform , s transform , time–frequency analysis , fractional fourier transform , computer science , gabor wavelet , artificial intelligence , mathematics , fourier analysis , algorithm , pattern recognition (psychology) , computer vision , mathematical analysis , pure mathematics , wavelet transform , wavelet packet decomposition , filter (signal processing) , wavelet , discrete wavelet transform
The affine Fourier transform (AFT) plays an important role in many fields of optics and signal processing. The Gabor transform (GT) is a kind of linear time–frequency representation (TFR). Compared with many bilinear TFRs, the GT does not have the cross‐term problem. In this study, the authors propose a time–frequency analysis method based on the AFT and GT. First, they obtain an affine relation between the AFT and the modified GT (MGT). Since the MGT is closely related to the AFT, they can use it as an assistant tool for signal processing in the AFT domain. Moreover, many useful relations between the AFT and the MGT are derived, such as recovery relation, projection relation and power integration relation. Then, they demonstrate that the AFT also has the affine relation with other TFRs, such as the Gabor–Wigner transform and the general class of quadratic distribution. Last, using the new time–frequency analysis method associated with the AFT and MGT, they present the filter design for multiple component chirp signal separation. Moreover, the simulation results illustrate the effectiveness of the proposed method.