• DocumentCode
    1026760
  • Title

    Parallel architecture for prototype training

  • Author

    Zhu, Mingda ; Loh, N. ; Khalaf, S. ; Siy, P.

  • Author_Institution
    Oakland University, Center for Robotics & Advanced Automation, Rochester, USA
  • Volume
    22
  • Issue
    21
  • fYear
    1986
  • Firstpage
    1100
  • Lastpage
    1102
  • Abstract
    The letter suggests an efficient parallel hardware architecture for prototype training in pattern recognition. Sample means and covariance matrices are computed by the same architecture and much attention is paid to the implementation of covariance matrices. A k2-chip of processor elements is used to implement covariance matrices.
  • Keywords
    computerised pattern recognition; parallel architectures; covariance matrices; k2-chip; parallel hardware architecture; pattern recognition; processor elements; prototype training;
  • fLanguage
    English
  • Journal_Title
    Electronics Letters
  • Publisher
    iet
  • ISSN
    0013-5194
  • Type

    jour

  • DOI
    10.1049/el:19860754
  • Filename
    4256968