• DocumentCode
    3213119
  • Title

    A novel self-adaptive differential evolution algorithm for efficient design of multiplier-less low-pass FIR filter

  • Author

    Chandra, A. ; Chattopadhyay, S.

  • Author_Institution
    Dept. of Electron. & Telecommun. Eng., Bengal Eng. & Sci. Univ., Shibpur, India
  • fYear
    2011
  • fDate
    20-22 July 2011
  • Firstpage
    733
  • Lastpage
    738
  • Abstract
    Variety of real-world optimization problems can be successfully solved by employing a powerful technique, called Differential Evolution (DE) algorithm. The popularity of DE has grown tremendously since its inception as it includes a very few number of control parameters. However, the selection or tuning of these parameters plays a crucial role in determining the performance of the algorithm in terms of its convergence behaviour. In this paper, a novel Self-Adaptive DE (SADE) approach has been proposed for the de sign of a multiplier-less low-pass linear-phase FIR filter to improve the computational efficiency of the algorithm. For this purpose, the convergence behaviour of the SADE technique has been presented and it has been compared with that of traditional DE technique. Additionally, the performance of the SADE-optimized filter has been evaluated in terms of its magnitude response. The corresponding magnitude response for the DE-optimized filter has also been presented for comparison. It has been established that the proposed SADE algorithm outperforms the traditional DEfor this particular design problem.
  • Keywords
    FIR filters; computational complexity; convergence; evolutionary computation; linear phase filters; low-pass filters; SADE algorithm; SADE approach; SADE technique; SADE-optimized filter; computational efficiency; control parameters; convergence behaviour; magnitude response; multiplier-less low-pass FIR filter; multiplier-less low-pass linear-phase FIR filter design; parameter selection; parameter tuning; powerful technique; real-world optimization problems; self-adaptive DE approach; self-adaptive differential evolution algorithm; Convergence speed; Cost function; Differential Evolution (DE); Multiplier-less FIR filter; Weighting Factor;
  • fLanguage
    English
  • Publisher
    iet
  • Conference_Titel
    Sustainable Energy and Intelligent Systems (SEISCON 2011), International Conference on
  • Conference_Location
    Chennai
  • Type

    conf

  • DOI
    10.1049/cp.2011.0460
  • Filename
    6143409