• DocumentCode
    3404950
  • Title

    Partial updating RLS algorithm

  • Author

    Jin, Minglia

  • Author_Institution
    Sch. of Electron. & Inf. Eng., Dalian Univ. of Technol., China
  • Volume
    1
  • fYear
    2004
  • fDate
    31 Aug.-4 Sept. 2004
  • Firstpage
    392
  • Abstract
    In this paper, a new computationally efficient algorithm for recursive least-squares (RLS) algorithm called reduced order RLS, it is also called as partial updating RLS (PU-RLS), algorithm is introduced. The basic idea of UP-RLS algorithm is that a high order filter function is decomposed into two low order simple functions, and then update the sub filter coefficients partially which result in less computation. This kind of adaptive algorithm shows much more enhanced computational efficiency compared to the earlier works such as split RLS algorithm but with better performance than split RLS algorithm based on simulation results.
  • Keywords
    adaptive filters; least squares approximations; recursive estimation; high order filter function; partial updating RLS algorithm; recursive least-squares algorithm; reduced order RLS; Adaptive algorithm; Adaptive filters; Computational efficiency; Interference cancellation; Lattices; Output feedback; Paper technology; Resonance light scattering; Signal generators; Transversal filters;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing, 2004. Proceedings. ICSP '04. 2004 7th International Conference on
  • Print_ISBN
    0-7803-8406-7
  • Type

    conf

  • DOI
    10.1109/ICOSP.2004.1452664
  • Filename
    1452664