Signal Enhancement by Time-Frequency Peak Filtering

Boualem Boashash, Mostefa Mesbah

Research output: Contribution to journalArticle

118 Citations (Scopus)

Abstract

Time-frequency peak filtering (TFPF) allows the reconstruction of signals from observations corrupted by additive noise by encoding the noisy signal as the instantaneous frequency (IF) of a frequency modulated (FM) analytic signal. IF estimation is then performed on the analytic signal using the peak of a time-frequency distribution (TFD) to recover the filtered signal. This method is biased when the peak of the Wigner-Ville distribution (WVD) is used to estimate the encoded signal's instantaneous frequency. We characterize a class of signals for which the method implemented using the pseudo WVD is approximately unbiased. This class contains deterministic bandlimited nonstationary multicomponent signals in additive white Gaussian noise (WGN). We then derive the pseudo WVD window length that gives a reduced bias when TFPF is used for signals from this class. Testing of the method on both synthetic and real life newborn electroencephalogram (EEG) signals shows clean recovery of the signals in noise level down to a signal-to-noise ratio (SNR) of - 9 dB.

Original languageEnglish
Pages (from-to)929-937
Number of pages9
JournalIEEE Transactions on Signal Processing
Volume52
Issue number4
DOIs
Publication statusPublished - Apr 2004

Keywords

  • Frequency modulation
  • IF estimation
  • Time-frequency filtering

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering

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