• DocumentCode
    3135362
  • Title

    An improverd variable step size LMS adaptive filtering algorithm

  • Author

    Pingping, Li ; TengDa, Pei ; BingNan, Pei ; LiJun, Hu

  • Author_Institution
    Sch. of Inf. Eng., Dalian Univ., Dalian, China
  • fYear
    2009
  • fDate
    20-21 Sept. 2009
  • Firstpage
    495
  • Lastpage
    497
  • Abstract
    LMS (least mean square) algorithm is widely used due to its simple and stable performance. As is well known, there is an inherent conflict between the convergence rate and steady-state misadjustment, which can be overcome through the adjustment of size factor. The paper has analyzed some LMS algorithms that already existed and a new improved variable step-size LMS algorithm is presented. The computer simulation results are consistent with the theoretic analysis, Which show that the algorithm not only has a faster convergence rate, but also has a smaller steady-state error.
  • Keywords
    adaptive filters; least mean squares methods; convergence rate; improved variable step size LMS adaptive filtering algorithm; least mean square algorithm; stead-state misadjustment; Adaptive filters; Algorithm design and analysis; Computer simulation; Convergence; Educational institutions; Equations; Error correction; Filtering algorithms; Least squares approximation; Steady-state; LMS algorithm; convergence rate; steady-state error; variable step-size;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information, Computing and Telecommunication, 2009. YC-ICT '09. IEEE Youth Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4244-5074-9
  • Electronic_ISBN
    978-1-4244-5076-3
  • Type

    conf

  • DOI
    10.1109/YCICT.2009.5382451
  • Filename
    5382451