• DocumentCode
    775350
  • Title

    Least squares order-recursive lattice smoothers

  • Author

    Yuan, Jenq-Tay ; Stuller, John A.

  • Author_Institution
    Dept. of Electron. Eng., Fu Jen Catholic Univ., Taipei, Taiwan
  • Volume
    43
  • Issue
    5
  • fYear
    1995
  • fDate
    5/1/1995 12:00:00 AM
  • Firstpage
    1058
  • Lastpage
    1067
  • Abstract
    Conventional least squares order-recursive lattice (LSORL) filters use present and past data values to estimate the present value of a signal. This paper introduces LSORL smoothers which use past, present and future data for that purpose. Except for an overall delay needed for physical realization, LSORL smoothers can substantially outperform LSORL filters while retaining all the advantages of an order-recursive structure
  • Keywords
    adaptive filters; lattice filters; least squares approximations; recursive filters; smoothing methods; adaptive LS lattice filters; delay; future data; least squares order-recursive lattice; order-recursive structure; past data; present data; recursive lattice filters; recursive lattice smoothers; Delay estimation; Estimation error; Finite impulse response filter; Kalman filters; Lattices; Least squares approximation; Least squares methods; Mean square error methods; Nonlinear filters; Transversal filters;
  • fLanguage
    English
  • Journal_Title
    Signal Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1053-587X
  • Type

    jour

  • DOI
    10.1109/78.382393
  • Filename
    382393
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=775350