A study of nonlinear time–varying spectral analysis based on HHT, MODWPT and multitaper time–frequency reassignment

  • Authors:
  • Pei-Wei Shan;Ming Li

  • Affiliations:
  • School of Information Science & Technology, East Normal University, Shanghai, China;School of Information Science & Technology, East Normal University, Shanghai, China

  • Venue:
  • ICCSA'10 Proceedings of the 2010 international conference on Computational Science and Its Applications - Volume Part II
  • Year:
  • 2010

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Abstract

Numerous approaches have been explored to improve the performance of time–frequency analysis and to provide a sufficiently clear time–frequency representation. Among them, three methods such as the empirical mode decomposition (EMD) with Hilbert transform (HT) (or termed as the Hilbert–Huang Transform (HHT)), along with the Hilbert spectrum based on maximal overlap discrete wavelet package transform (MODWPT) and the multitaper time–frequency reassignment raised by Xiao and Flandrin, are noteworthy. This study evaluates the performances of three transforms mentioned above, in estimating single and multicomponent chip signals in the presence of noise or noise–free. Rényi Enropy is implemented for measuring the effectiveness of each algorithm. The paper demonstrates that under these conditions MODWPT owes better time–frequency resolution and statistical stability than the HHT. The multitaper time–frequency reassigned spectrogram makes excellent trade–off between time–frequency localization and local stationarity.