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Parametric modeling for damped sinusoids from multiple channels

  • Zhenhua Zhou
  • , H. C. So
  • , Mads Grasboll Christensen

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

Abstract

The problem of parametric modeling for noisy damped sinusoidal signals from multiple channels is addressed. Utilizing the shift invariance property of the signal subspace, the number of distinct sinusoidal poles in the multiple channels is first determined. With the estimated number, the distinct frequencies and damping factors are then computed with the multi-channel weighted linear prediction method. The estimated sinusoidal poles are then matched to each channel according to the extreme value theory of distribution of random fields. Simulations are performed to show the performance advantages of the proposed multi-channel sinusoidal modeling methodology compared with existing methods. © 1991-2012 IEEE.
Original languageEnglish
Article number6509467
Pages (from-to)3895-3907
JournalIEEE Transactions on Signal Processing
Volume61
Issue number15
DOIs
Publication statusPublished - 2013

Research Keywords

  • Extreme value theory
  • model order estimation
  • multi-channel processing
  • sinusoidal model selection
  • sinusoidal parameter estimation
  • weighted linear prediction

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