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Nonlinear squeezing transform for weak signal detection

  • Xi'an Jiaotong University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

We introduce a novel algorithm, called nonlinear squeezing transform, to characterize the time-frequency pattern of nonstationary multi-component signals, especially for weak component detection. As a generally known, conventional time-frequency analysis (TFA) methods can characterize the time-frequency pattern of nonstationary signal. However, it is difficult to detect the weak component hidden in complex signals because the time-frequency information is influenced by the amplitude of the signal. Inspired by the calculation procedure of instantaneous frequency in the synchro-squeezing transform, nonlinear squeezing transform is presented, which is only relevant to the phase but is independent of the signal amplitude. The experiment on real signal shows that the method can effectively detect the weak component in complex signals, and the comparison study with some TFA methods also shows the advantages in weak signal detection.

Original languageEnglish
Title of host publication2014 IEEE China Summit and International Conference on Signal and Information Processing, IEEE ChinaSIP 2014 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages718-722
Number of pages5
ISBN (Electronic)9781479954032
DOIs
StatePublished - 3 Sep 2014
Event2nd IEEE China Summit and International Conference on Signal and Information Processing, IEEE ChinaSIP 2014 - Xi'an, China
Duration: 9 Jul 201413 Jul 2014

Publication series

Name2014 IEEE China Summit and International Conference on Signal and Information Processing, IEEE ChinaSIP 2014 - Proceedings

Conference

Conference2nd IEEE China Summit and International Conference on Signal and Information Processing, IEEE ChinaSIP 2014
Country/TerritoryChina
CityXi'an
Period9/07/1413/07/14

Keywords

  • Time-frequency analysis
  • instantaneous frequency
  • multi-component signal
  • signal detection
  • synchrosqueezing transform

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