• DocumentCode
    1805628
  • Title

    A fuzzy classifier based on probabilistic relaxation

  • Author

    Fu, Alan M N ; Yan, Hong

  • Author_Institution
    Dept. of Electr. & Inf. Eng., Sydney Univ., NSW, Australia
  • Volume
    6
  • fYear
    1999
  • fDate
    36342
  • Firstpage
    4351
  • Abstract
    In this paper, a new fuzzy classifier is developed in which a simple relation between probabilistic vectors and fuzzy sets is derived and the probabilistic relaxation scheme is employed. The fuzzy classifier consists of two stages. Firstly, the fuzzy sets are separated into several groups in terms of the relation between probabilistic vectors and fuzzy sets. Secondly, each group of fuzzy sets is further classified into different subgroups by the probabilistic relaxation scheme. Numerical experiments to verify the effectiveness of the proposed method are carried out. The results show that the method is simple and works well
  • Keywords
    fuzzy set theory; pattern classification; probability; relaxation theory; fuzzy classifier; fuzzy sets; probabilistic relaxation; probabilistic vectors; Australia; Clustering methods; Fuzzy neural networks; Fuzzy sets; Information processing; Labeling; Layout; Neural networks; Noise shaping; Random variables;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 1999. IJCNN '99. International Joint Conference on
  • Conference_Location
    Washington, DC
  • ISSN
    1098-7576
  • Print_ISBN
    0-7803-5529-6
  • Type

    conf

  • DOI
    10.1109/IJCNN.1999.830868
  • Filename
    830868