• DocumentCode
    328327
  • Title

    Fuzzy neural networks based on spline functions

  • Author

    Shimojima, Koji ; Fukuda, Toshio ; Arai, Fumihito

  • Author_Institution
    Dept. of Mechano-Inf. & Syst., Nagoya Univ., Japan
  • Volume
    1
  • fYear
    1993
  • fDate
    25-29 Oct. 1993
  • Firstpage
    754
  • Abstract
    Recently, fuzzy systems are used in many fields and places. In order to apply the fuzzy systems to wider fields, it is necessary to study the tuning methods of the fuzzy system. Some self-tuning methods have been proposed so far. However these conventional self-tuning methods do not have sufficient capability of generalization. In this paper, we propose a new self-tuning fuzzy neural network. The fuzzy neural network consists of membership functions that are expressed by spline functions. The delta rule is applied to tune the membership functions and consequent parts. The effectiveness of the proposed methods is shown by some numerical examples.
  • Keywords
    fuzzy neural nets; generalisation (artificial intelligence); learning (artificial intelligence); self-adjusting systems; splines (mathematics); delta rule; fuzzy neural networks; generalization; learning algorithm; membership functions; self-tuning; spline function; Biomedical engineering; Fuzzy control; Fuzzy logic; Fuzzy neural networks; Fuzzy reasoning; Fuzzy systems; Input variables; Shape; Spline; Tuning;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 1993. IJCNN '93-Nagoya. Proceedings of 1993 International Joint Conference on
  • Print_ISBN
    0-7803-1421-2
  • Type

    conf

  • DOI
    10.1109/IJCNN.1993.714023
  • Filename
    714023