Efficient Analysis of Time-Varying Multicomponent Signals with Modified LPTFT

<p/> <p>This paper presents efficient algorithms for the analysis of nonstationary multicomponent signals based on modified local polynomial time-frequency transform. The signals to be analyzed are divided into a number of segments and the desired parameters for computing modified the lo...

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Main Authors: Wei Yongmei, Bi Guoan
Format: Article
Language:English
Published: SpringerOpen 2005-01-01
Series:EURASIP Journal on Advances in Signal Processing
Subjects:
Online Access:http://dx.doi.org/10.1155/ASP.2005.1261
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spelling doaj-9b90e41c0a354e90a195ce5f235f238a2020-11-25T00:37:53ZengSpringerOpenEURASIP Journal on Advances in Signal Processing1687-61721687-61802005-01-0120058784762Efficient Analysis of Time-Varying Multicomponent Signals with Modified LPTFTWei YongmeiBi Guoan<p/> <p>This paper presents efficient algorithms for the analysis of nonstationary multicomponent signals based on modified local polynomial time-frequency transform. The signals to be analyzed are divided into a number of segments and the desired parameters for computing modified the local polynomial time-frequency transform in each segment are estimated from polynomial Fourier transform in the frequency domain. Compared to other reported algorithms, the length of overlap between consecutive segments is reduced to minimize the overall computational complexity. The concept of adaptive window lengths is also employed to achieve a better time-frequency resolution for each component. Numerical simulations with synthesized multicomponent signals show that the proposed ones achieve better performance on instantaneous frequency estimation with greatly reduced computational complexity.</p>http://dx.doi.org/10.1155/ASP.2005.1261time-frequency analysistime varyingmulticomponentmodified LPTFTimpulse noise
collection DOAJ
language English
format Article
sources DOAJ
author Wei Yongmei
Bi Guoan
spellingShingle Wei Yongmei
Bi Guoan
Efficient Analysis of Time-Varying Multicomponent Signals with Modified LPTFT
EURASIP Journal on Advances in Signal Processing
time-frequency analysis
time varying
multicomponent
modified LPTFT
impulse noise
author_facet Wei Yongmei
Bi Guoan
author_sort Wei Yongmei
title Efficient Analysis of Time-Varying Multicomponent Signals with Modified LPTFT
title_short Efficient Analysis of Time-Varying Multicomponent Signals with Modified LPTFT
title_full Efficient Analysis of Time-Varying Multicomponent Signals with Modified LPTFT
title_fullStr Efficient Analysis of Time-Varying Multicomponent Signals with Modified LPTFT
title_full_unstemmed Efficient Analysis of Time-Varying Multicomponent Signals with Modified LPTFT
title_sort efficient analysis of time-varying multicomponent signals with modified lptft
publisher SpringerOpen
series EURASIP Journal on Advances in Signal Processing
issn 1687-6172
1687-6180
publishDate 2005-01-01
description <p/> <p>This paper presents efficient algorithms for the analysis of nonstationary multicomponent signals based on modified local polynomial time-frequency transform. The signals to be analyzed are divided into a number of segments and the desired parameters for computing modified the local polynomial time-frequency transform in each segment are estimated from polynomial Fourier transform in the frequency domain. Compared to other reported algorithms, the length of overlap between consecutive segments is reduced to minimize the overall computational complexity. The concept of adaptive window lengths is also employed to achieve a better time-frequency resolution for each component. Numerical simulations with synthesized multicomponent signals show that the proposed ones achieve better performance on instantaneous frequency estimation with greatly reduced computational complexity.</p>
topic time-frequency analysis
time varying
multicomponent
modified LPTFT
impulse noise
url http://dx.doi.org/10.1155/ASP.2005.1261
work_keys_str_mv AT weiyongmei efficientanalysisoftimevaryingmulticomponentsignalswithmodifiedlptft
AT biguoan efficientanalysisoftimevaryingmulticomponentsignalswithmodifiedlptft
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