• DocumentCode
    389670
  • Title

    An improved adaptive neural network and its application on random shape

  • Author

    Mo, Can-Lin ; Tan, Jian-Rong

  • Author_Institution
    State Key Lab. of CAD & CG, Zhejiang Univ., China
  • Volume
    1
  • fYear
    2002
  • fDate
    2002
  • Firstpage
    91
  • Abstract
    The random shape generation method is put forward based on adaptive neural networks. The adaptive neural network is trained from an arbitrary regular geometric shape during the random deformation process. Thus, the regular shape can be changed to an irregular one with the adaptive learning method, and the global and local controllability can both be enhanced. With an improvement on the traditional adaptive neural network algorithm, certainty and randomness can be fully combined, so that fuzzy controllability and adjustability can be dominated easily and concisely.
  • Keywords
    adaptive control; computational geometry; controllability; neurocontrollers; shape control; adaptive learning method; adaptive neural network; certainty; free shape; fuzzy adjustability; fuzzy controllability; global controllability; local controllability; neural network training; random deformation process; random shape generation method; randomness; Adaptive control; Adaptive systems; Artificial neural networks; Controllability; Fractals; Fuzzy control; Neural networks; Programmable control; Shape control; Solid modeling;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics, 2002. Proceedings. 2002 International Conference on
  • Print_ISBN
    0-7803-7508-4
  • Type

    conf

  • DOI
    10.1109/ICMLC.2002.1176716
  • Filename
    1176716