• DocumentCode
    2621517
  • Title

    A new signal estimation algorithm for use in Wiener filtering

  • Author

    Lindquist, Claude S. ; Powell, Clinton C.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Miami Univ., Coral Gables, FL, USA
  • fYear
    1990
  • fDate
    1-3 May 1990
  • Firstpage
    2124
  • Abstract
    A nonlinear smoothing algorithm is presented for determining signal autocorrelation and power spectral density matrices. The algorithm can be utilized to generate matrix filters. It is used to form a Wiener estimation filter. Simulations are presented to confirm the usefulness of the smoothing algorithm and to suggest a time-varying memoryless filter approach
  • Keywords
    computerised signal processing; digital filters; digital simulation; estimation theory; filtering and prediction theory; signal detection; smoothing circuits; Wiener estimation filter; Wiener filtering; matrix filters; nonlinear smoothing algorithm; power spectral density matrices; signal autocorrelation; signal estimation algorithm; time-varying memoryless filter; Autocorrelation; Ear; Estimation; Filtering algorithms; Frequency domain analysis; Noise reduction; Smoothing methods; Stochastic resonance; Wiener filter;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Circuits and Systems, 1990., IEEE International Symposium on
  • Conference_Location
    New Orleans, LA
  • Type

    conf

  • DOI
    10.1109/ISCAS.1990.112232
  • Filename
    112232