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Minimum variance spectral estimation-based time frequency analysis for nonstationary time-series

  • S. C. Chan*
  • , Z. G. Zhang
  • , K. M. Tsui
  • *Corresponding author for this work
  • The University of Hong Kong

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

Abstract

This paper introduces two new time-frequency analysis methods originated from the minimum variance spectral estimation (MVSE) for nonstationary time-series. First, a windowed MVSE (WMVSE) extends the conventional MVSE by windowing the observation data to obtain a timefrequency distribution for the time-series. Moreover, the window lengths are selected adaptively by the intersection of confidence intervals (ICI) rule to improve the time-frequency resolution. Secondly, a new recursive MVSE (RMVSE) is developed to process the input samples recursively at a lower arithmetic complexity for online time-frequency analysis. Simulation results show that the proposed WMVSE with adaptive windows offers better frequency resolutions than the Fourier-transformed-based time-frequency distributions, and the RMVSE has a good performance when tracking sinusoidal signals.

Original languageEnglish
Title of host publication2007 IEEE International Symposium on Circuits and Systems, ISCAS 2007
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1815-1818
Number of pages4
ISBN (Print)1424409209
DOIs
StatePublished - 2007
Externally publishedYes
Event2007 IEEE International Symposium on Circuits and Systems, ISCAS 2007 - New Orleans, LA, United States
Duration: 27 May 200730 May 2007

Publication series

NameProceedings - IEEE International Symposium on Circuits and Systems
ISSN (Print)0271-4310

Conference

Conference2007 IEEE International Symposium on Circuits and Systems, ISCAS 2007
Country/TerritoryUnited States
CityNew Orleans, LA
Period27/05/0730/05/07

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