Multitaper Covariance Estimation and Spectral Denoising

@article{Erdol2005MultitaperCE,
  title={Multitaper Covariance Estimation and Spectral Denoising},
  author={Nurgun Erdol and Tuncay Gunes},
  journal={Conference Record of the Thirty-Ninth Asilomar Conference onSignals, Systems and Computers, 2005.},
  year={2005},
  pages={1144-1147}
}
A seamless and smooth transition from nonparametric multitaper (MT) spectral estimation (SE) to autoregressive (AR) parametrization is made possible via autocorrelation estimates from multitapered data. We show that AR spectral estimates obtained from MT autocorrelation estimates outperform the conventional method and the Capon-AR estimates. We derive a direct method of autocorrelation estimation from multitapered data. We show that choice of tapers yields low-bias and consistent… CONTINUE READING
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Spectral Analysis of Signals

  • P. Stoica, R. Moses
  • 2005
2 Excerpts

A Theory of Polyspectra for Nonstationary Stochastic Processes

  • A. Hannsen, L. Scharf
  • IEEE Tran. Sig. Proc., Vol.51,
  • 2000
1 Excerpt

Statistical Digital Signal Processing and Modeling

  • M. H. Hayes
  • John-Wiley and Sons, INC
  • 1996
3 Excerpts

Spectral Analysis for Physical Applications

  • D. B. Percival, A. T. Walden
  • 1993
2 Excerpts

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