• DocumentCode
    3069504
  • Title

    On the asymptotic normality of autoregressive spectral density estimates for the noise corrupted case

  • Author

    Gingras, D.F.

  • Author_Institution
    Naval Ocean Systems Center, San Diego, California
  • Volume
    9
  • fYear
    1984
  • fDate
    30742
  • Firstpage
    604
  • Lastpage
    607
  • Abstract
    Asymptotic statistics for spectral density estimates of noise corrupted autoregressive (AR) series are evaluated. The "high-order" Yule-Walker equation estimates of the autoregressive parameters are used to form a spectral density estimate. The estimate is shown to be a consistent asymptotically normal (CAN) estimate. An expression for the variance of the limiting distribution in terms of the AR process parameters and the noise variance is provided.
  • Keywords
    Additive noise; Additive white noise; Autoregressive processes; Computer aided software engineering; Density functional theory; Equations; Oceans; Statistical distributions; Statistics; Tiles;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech, and Signal Processing, IEEE International Conference on ICASSP '84.
  • Type

    conf

  • DOI
    10.1109/ICASSP.1984.1172326
  • Filename
    1172326