• DocumentCode
    1458772
  • Title

    Fuzzy hyperline segment clustering neural network

  • Author

    Kulkarni, U.V. ; Sontakke, T.R. ; Kulkarni, A.B.

  • Author_Institution
    Dept. of Electron. & Comput. Sci., SGGS Coll. of Eng., Nanded, India
  • Volume
    37
  • Issue
    5
  • fYear
    2001
  • fDate
    3/1/2001 12:00:00 AM
  • Firstpage
    301
  • Lastpage
    303
  • Abstract
    A fuzzy hyperline segment clustering neural network (FHLSCNN) and its learning algorithm is proposed. This algorithm can learn ill-defined nonlinear cluster boundaries in a few passes and is suitable for on-line cluster boundaries in a few passes and is suitable for on-line adaption. The FHLSCNN is superior compared to the fuzzy min-max clustering neural network (FMN) proposed by Simpson
  • Keywords
    fuzzy neural nets; learning (artificial intelligence); pattern clustering; fuzzy hyperline segment clustering neural network; learning algorithm;
  • fLanguage
    English
  • Journal_Title
    Electronics Letters
  • Publisher
    iet
  • ISSN
    0013-5194
  • Type

    jour

  • DOI
    10.1049/el:20010198
  • Filename
    911967
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1458772