• DocumentCode
    341403
  • Title

    Transform domain neural filters

  • Author

    Nakanishi, Isao ; Itoh, Yoshio ; Fukui, Yutaka

  • Author_Institution
    Fac. of Educ., Tottori Univ., Japan
  • Volume
    5
  • fYear
    1999
  • fDate
    1999
  • Firstpage
    579
  • Abstract
    A neural filter is effective for the system identification of a nonlinear system and the noise reduction in a nonlinear signal. However, the neural filter requires large number of iterations for convergence. This paper presents new structures of the multi-layered neural filter (Transform Domain Neural Filter; TDNF) where the orthonormal transform is introduced to accelerate the convergence speed. In the TDNF (i), the input signal is transformed by the orthonormal transform, then led to the input layer of the neural filter. The TDNF (ii) adopts the orthonormal transform in all inter-layers. Through the computer simulation in the nonlinear system identification, it is confirmed that the introduction of the orthonormal transform is effective for the speed-up of convergence in the neural filter
  • Keywords
    convergence; filtering theory; identification; interference suppression; neural nets; nonlinear systems; signal processing; transforms; convergence speed; multilayered neural filter; noise reduction; nonlinear signal; nonlinear system; orthonormal transform; system identification; transform domain neural filters; Acceleration; Adaptive filters; Autocorrelation; Convergence; Discrete transforms; Eigenvalues and eigenfunctions; Neural networks; Nonlinear filters; Signal processing; System identification;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Circuits and Systems, 1999. ISCAS '99. Proceedings of the 1999 IEEE International Symposium on
  • Conference_Location
    Orlando, FL
  • Print_ISBN
    0-7803-5471-0
  • Type

    conf

  • DOI
    10.1109/ISCAS.1999.777638
  • Filename
    777638