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AuthorAwal, Md Abdul
AuthorOuelha, Samir
AuthorDong, Shiying
AuthorBoashash, B.
Available date2020-09-24T08:11:57Z
Publication Date2017
Publication NameDigital Signal Processing: A Review Journal
ResourceScopus
ISSN10512004
URIhttp://dx.doi.org/10.1016/j.dsp.2017.07.022
URIhttp://hdl.handle.net/10576/16284
AbstractThe Locally Optimized Spectrogram (LOS) defines a novel method for obtaining a high-resolution time-frequency (t,f) representation based on the short-time fractional Fourier transform (STFrFT). The key novelty of the LOS is that it automatically determines the locally optimal window parameters and fractional order (angle) for all signal components, leading to a high-resolution and cross-terms free time-frequency representation. This method is suitable for multicomponent and non-stationary signals without a priori signal information. Simulated signals, real biomedical applications, and various measures are used to validate the improved performance of the LOS and compare it with other state-of-the-art methods. The robustness of the LOS is also demonstrated under different signal-to-noise ratio (SNR) conditions. Finally, the relationship between the LOS and other time-frequency distributions (TFDs) is depicted and a recursive formulation is presented and shows the trade-off between the cross-terms suppression and auto-terms resolution. 1 2017 Elsevier Inc.
SponsorThis work was supported in part by a Grant from the Qatar National Research Fund under its National Priorities Research Program award nos NPRP 4-1303-2-517 and NPRP 6-885-2-364 . The authors wish to thank Professor Paul Colditz for his role in providing the data that were used in this study. Appendix A
Languageen
PublisherElsevier Inc.
SubjectEnergy concentration
Fractional S-method (FrSM)
Instantaneous frequency (IF) estimation
Local optimization
Quadratic time-frequency distribution (QTFD)
Short-time fractional Fourier transform (STFrFT)
TitleA robust high-resolution time-frequency representation based on the local optimization of the short-time fractional Fourier transform
TypeArticle
Pagination125-144
Volume Number70
dc.accessType Abstract Only


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