• DocumentCode
    1752947
  • Title

    A Novel Neural Networks-Based Approach for Designing FIR Filters

  • Author

    Wang, Xiaohua ; Meng, Xianzhi ; He, Yigang

  • Author_Institution
    Coll. of Electr. & Inf. Eng., Changsha Univ. of Sci. & Technol.
  • Volume
    1
  • fYear
    0
  • fDate
    0-0 0
  • Firstpage
    4029
  • Lastpage
    4032
  • Abstract
    A novel linear-phase finite-impulse response (FIR) digital filters design approach based on neural networks optimization technique was proposed in this paper. The main idea is to minimize the weighted square-error function in the frequency-domain. The convergence theorem of the neural networks algorithm was presented and proved to illustrate the proposed algorithm stable, and the implementation of the approach was also described together with some design guidelines. This method can control the overshoot phenomenon that may happen near the pass-band and stop-band edge of the designed filter. Some optimal design examples were given to illustrate the effectiveness of the proposed optimal design method
  • Keywords
    FIR filters; linear phase filters; neural nets; convergence theorem; frequency domain; linear-phase finite-impulse response digital filters; neural network optimization; weighted square-error function; Algorithm design and analysis; Convergence; Design engineering; Digital filters; Educational institutions; Finite impulse response filter; Frequency; Least squares methods; Neural networks; Sampling methods; FIR filter; Neural networks; convergence theorem; optimal design;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on
  • Conference_Location
    Dalian
  • Print_ISBN
    1-4244-0332-4
  • Type

    conf

  • DOI
    10.1109/WCICA.2006.1713130
  • Filename
    1713130