• DocumentCode
    1641917
  • Title

    Wavelets as a regularization technique for spectral density estimation

  • Author

    Moulin, Pierre

  • Author_Institution
    Bell Commun. Res., Morristown, NJ, USA
  • fYear
    1992
  • Firstpage
    73
  • Lastpage
    76
  • Abstract
    Estimation of the spectral density S(f) of a stationary random process can be viewed as a nonparametric statistical estimation problem. A nonparametric approach based on a wavelet representation for the logarithm of the unknown S(f) is introduced. This approach offers the ability to capture significant components of S(f) at different resolution levels by application of a significance test, and guarantees nonnegativity of the spectral density estimator
  • Keywords
    random processes; spectral analysis; statistical analysis; wavelet transforms; logarithm; nonparametric statistical estimation; regularization technique; significance test; spectral density estimation; spectral density estimator; stationary random process; wavelet representation; wavelets; Additive noise; Maximum likelihood estimation; Probability density function; Random processes; Random variables; Signal resolution; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Time-Frequency and Time-Scale Analysis, 1992., Proceedings of the IEEE-SP International Symposium
  • Conference_Location
    Victoria, BC
  • Print_ISBN
    0-7803-0805-0
  • Type

    conf

  • DOI
    10.1109/TFTSA.1992.274231
  • Filename
    274231
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1641917