Journal
PLOS ONE
Volume 17, Issue 11, Pages -Publisher
PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pone.0278223
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Funding
- Science and Technology Innovation Project of Colleges and Universities in Shanxi Province(China) [2020L0301]
- Fundamental Research Program of Shanxi Province(China) [20210302124545]
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This study proposes a new TFA method called LMSBCT, which can handle nonstationary signals effectively and achieve better concentration in terms of time-frequency energy and instantaneous frequency trajectory. Numerical simulations and real experiments demonstrate the superiority of this method.
In recent years, time-frequency analysis (TFA) methods have received widespread attention and undergone rapid development. However, traditional TFA methods cannot achieve the desired effect when dealing with nonstationary signals. Therefore, this study proposes a new TFA method called the local maximum synchrosqueezing scaling-basis chirplet transform (LMSBCT), which is a further improvement of the scaling-basis chirplet transform (SBCT) with energy rearrangement in frequency and can be viewed as a good combination of SBCT and local maximum synchrosqueezing transform. A better concentration in terms of the time-frequency energy and a more accurate instantaneous frequency trajectory can be achieved using LMSBCT. The time-frequency distribution of strong frequency-modulated signals and multicomponent signals can be handled well, even for signals with close signal frequencies and low signal-to-noise ratios. Numerical simulations and real experiments were conducted to prove the superiority of the proposed method over traditional methods.
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