Local maximum synchrosqueezes form scaling-basis chirplet transform
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 maxi...
Main Authors: | , , , |
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Format: | Article |
Language: | English |
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Public Library of Science (PLoS)
2022-01-01
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Series: | PLoS ONE |
Online Access: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9707797/?tool=EBI |
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author | Yating Hou Liming Wang Xiuli Luo Xingcheng Han |
author_facet | Yating Hou Liming Wang Xiuli Luo Xingcheng Han |
author_sort | Yating Hou |
collection | DOAJ |
description | 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. |
first_indexed | 2024-04-11T07:46:14Z |
format | Article |
id | doaj.art-79847fb22fa247d086f9069c7fbcd19b |
institution | Directory Open Access Journal |
issn | 1932-6203 |
language | English |
last_indexed | 2024-04-11T07:46:14Z |
publishDate | 2022-01-01 |
publisher | Public Library of Science (PLoS) |
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series | PLoS ONE |
spelling | doaj.art-79847fb22fa247d086f9069c7fbcd19b2022-12-22T04:36:16ZengPublic Library of Science (PLoS)PLoS ONE1932-62032022-01-011711Local maximum synchrosqueezes form scaling-basis chirplet transformYating HouLiming WangXiuli LuoXingcheng HanIn 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.https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9707797/?tool=EBI |
spellingShingle | Yating Hou Liming Wang Xiuli Luo Xingcheng Han Local maximum synchrosqueezes form scaling-basis chirplet transform PLoS ONE |
title | Local maximum synchrosqueezes form scaling-basis chirplet transform |
title_full | Local maximum synchrosqueezes form scaling-basis chirplet transform |
title_fullStr | Local maximum synchrosqueezes form scaling-basis chirplet transform |
title_full_unstemmed | Local maximum synchrosqueezes form scaling-basis chirplet transform |
title_short | Local maximum synchrosqueezes form scaling-basis chirplet transform |
title_sort | local maximum synchrosqueezes form scaling basis chirplet transform |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9707797/?tool=EBI |
work_keys_str_mv | AT yatinghou localmaximumsynchrosqueezesformscalingbasischirplettransform AT limingwang localmaximumsynchrosqueezesformscalingbasischirplettransform AT xiuliluo localmaximumsynchrosqueezesformscalingbasischirplettransform AT xingchenghan localmaximumsynchrosqueezesformscalingbasischirplettransform |