• DocumentCode
    3500565
  • Title

    An improved variable step size LMS algorithm

  • Author

    Xueli Wu ; Liang Gao ; Zizhong Tan

  • Author_Institution
    Inst. of Electr. Eng., Yanshan Univ., Qinhuangdao, China
  • Volume
    01
  • fYear
    2013
  • fDate
    16-18 Aug. 2013
  • Firstpage
    533
  • Lastpage
    536
  • Abstract
    The traditional variable step size least mean square (LMS) algorithm has many weakness, such as poor convergence speed and susceptible to noise interference. In order to improve the performance of the algorithm, an improved variable step size LMS algorithm is presented, and it is applied to the noise cancelling system of communication. By using the hyperbolic tangent function, the relationship between step size and error signal is established. In this algorithm, the step size factor is adjusted by the absolute value of the product of the current and former errors. The algorithm also introduces the disturbance of the absolute estimation error to update the tapping vector of the self-adaptive filter. The simulation results show that the proposed algorithm has a faster convergence speed than traditional LMS algorithm and CTanh-LMS algorithm. And it obtains a good results in the noise cancelling system of communication.
  • Keywords
    adaptive filters; algorithm theory; interference suppression; least mean squares methods; CTanh-LMS algorithm; absolute estimation error; error signal; hyperbolic tangent function; noise cancelling system; noise interference; self-adaptive filter; step size factor; tapping vector; variable step size LMS algorithm; variable step size least mean square algorithm; Noise; Optimization; adaptive filter; hyperbolic tangent function; least mean square(LMS) algorithm; variable step size;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Measurement, Information and Control (ICMIC), 2013 International Conference on
  • Conference_Location
    Harbin
  • Print_ISBN
    978-1-4799-1390-9
  • Type

    conf

  • DOI
    10.1109/MIC.2013.6758020
  • Filename
    6758020