• DocumentCode
    1385030
  • Title

    A fuzzy clustering neural networks (FCNs) system design methodology

  • Author

    Zhang, David ; Pal, Sankar K.

  • Author_Institution
    Dept. of Comput., Hong Kong Polytech. Univ., Kowloon, China
  • Volume
    11
  • Issue
    5
  • fYear
    2000
  • fDate
    9/1/2000 12:00:00 AM
  • Firstpage
    1174
  • Lastpage
    1177
  • Abstract
    A system design methodology for fuzzy clustering neural networks (FCNs) is presented. This methodology emphasizes coordination between FCN model definition, architectural description, and systolic implementation. Two mapping strategies both from FCN model to system architecture and from the given architecture to systolic arrays are described. The effectiveness of the methodology is illustrated by: 1) applying the design to an effective FCN model; 2) developing the corresponding parallel architecture with special feedforward and feedback paths; and 3) building the systolic array suitable for VLSI implementation
  • Keywords
    VLSI; fuzzy neural nets; neural net architecture; systolic arrays; VLSI; architectural description; clustering; fuzzy clustering neural networks; parallel architecture; system design; systolic arrays; Computational modeling; Euclidean distance; Fuzzy neural networks; Fuzzy systems; Joining processes; Neural networks; Neurofeedback; Parallel architectures; Systolic arrays; Very large scale integration;
  • fLanguage
    English
  • Journal_Title
    Neural Networks, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1045-9227
  • Type

    jour

  • DOI
    10.1109/72.870048
  • Filename
    870048