• DocumentCode
    325193
  • Title

    Noise rejection in parameters identification for piecewise linear fuzzy models

  • Author

    Simani, S. ; Fantuzzi, C. ; Rovatti, R. ; Beghelli, S.

  • Author_Institution
    Eng. Dept., Ferrara Univ., Italy
  • Volume
    1
  • fYear
    1998
  • fDate
    4-9 May 1998
  • Firstpage
    378
  • Abstract
    The fuzzy model identification problem from noisy data is addressed. The piecewise linear fuzzy model structure is used as a nonlinear prototype for a multi-input, single-output unknown system. The consequent of the fuzzy model is identified using noisy data, e.g. collected from experiments on a real system. The identification procedure is formulated within the Frisch scheme, well established for linear systems, which has been modified and improved to be applied in fuzzy systems field
  • Keywords
    fuzzy systems; multivariable systems; noise; parameter estimation; uncertain systems; Frisch scheme; multi-input single-output unknown system; noise rejection; noisy data; parameters identification; piecewise linear fuzzy models; Ear; Fuzzy systems; Least squares methods; Linear systems; Linearity; Noise reduction; Parameter estimation; Piecewise linear approximation; Piecewise linear techniques; Systems engineering and theory;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems Proceedings, 1998. IEEE World Congress on Computational Intelligence., The 1998 IEEE International Conference on
  • Conference_Location
    Anchorage, AK
  • ISSN
    1098-7584
  • Print_ISBN
    0-7803-4863-X
  • Type

    conf

  • DOI
    10.1109/FUZZY.1998.687515
  • Filename
    687515