• DocumentCode
    2167977
  • Title

    An associative memory model for unsupervised sequence processing

  • Author

    Pantazi, Stefan V. ; Moehr, Jochen R.

  • Author_Institution
    Sch. of Health Inf. Sci., Victoria Univ., BC, Canada
  • fYear
    2005
  • fDate
    24-26 Aug. 2005
  • Firstpage
    233
  • Lastpage
    236
  • Abstract
    We introduce the design principles and present formally the building block of an associative memory model capable of unsupervised sequence processing: the constrained partially ordered set. We then use the model in a series of experiments, presented in increasing order of complexity and conclude that it demonstrates interesting information processing capabilities which warrant future development.
  • Keywords
    information theory; associative memory model; unsupervised sequence processing; Associative memory; Computational modeling; Computer science; Distributed processing; Fasteners; Information processing; Information retrieval; Information science; Information theory; Probability distribution;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Communications, Computers and signal Processing, 2005. PACRIM. 2005 IEEE Pacific Rim Conference on
  • Print_ISBN
    0-7803-9195-0
  • Type

    conf

  • DOI
    10.1109/PACRIM.2005.1517268
  • Filename
    1517268