• DocumentCode
    393558
  • Title

    System identification via simultaneous perturbation stochastic approximation

  • Author

    Hirokami, Tatsuya ; Maeda, Yutaka

  • Author_Institution
    Dept. of Electr. Eng., Kansai Univ., Suita, Japan
  • Volume
    2
  • fYear
    2002
  • fDate
    5-7 Aug. 2002
  • Firstpage
    1231
  • Abstract
    The simultaneous perturbation stochastic approximation (SPSA) is an extension of Kiefer-Wolfowitz stochastic approximation (KWSA) algorithm. In SPSA, since all parameters are perturbed simultaneously, it is possible to modify the parameters with only two measurements of the evaluation function disregard of the dimension of the parameters. We propose a parameter identification algorithm using SPSA. Simulation result shows the feasibility of the identification approach proposed.
  • Keywords
    approximation theory; discrete time systems; linear systems; parameter estimation; stochastic processes; Kiefer Wolfowitz stochastic approximation algorithm; discrete linear system; parameter estimation; simultaneous perturbation; simultaneous perturbation stochastic approximation; stochastic approximation; system identification; Delay effects; Delay estimation; Equations; Linear systems; Neural networks; Noise measurement; Parameter estimation; Stochastic processes; Stochastic systems; White noise;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    SICE 2002. Proceedings of the 41st SICE Annual Conference
  • Print_ISBN
    0-7803-7631-5
  • Type

    conf

  • DOI
    10.1109/SICE.2002.1195360
  • Filename
    1195360