• DocumentCode
    1615507
  • Title

    LBAQ: a pattern recognition neural network that learns by asking questions

  • Author

    Abou-Nasr, M.A. ; Sid-Ahmed, M.A.

  • Author_Institution
    Dept. of Electr. Eng., Windsor Univ., Ont., Canada
  • fYear
    1992
  • Firstpage
    1524
  • Abstract
    LBAQ (learning by asking questions) is a fast learning neural architecture that forms internal representations of the given examples and asks the teacher about labels for each of them. A considerable reduction in the length of the training session is achieved with LBAQ on the order of 1:500 over the time needed by a backpropagation network. The simulation performance results of this network on standard problems are superior to those for backpropagation networks in terms of ease, speed of training, and the ability to incrementally train the network on subjects of the training set at different times as opposed to the lengthy one-shot training session in the backpropagation case
  • Keywords
    learning by example; neural nets; pattern recognition; LBAQ; internal representations; learning by asking questions; neural architecture; pattern recognition neural network; training session; training set; Backpropagation algorithms; Clustering algorithms; Education; Intelligent robots; Neural networks; Pattern analysis; Pattern recognition; Relays; Resonance;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Circuits and Systems, 1992., Proceedings of the 35th Midwest Symposium on
  • Conference_Location
    Washington, DC
  • Print_ISBN
    0-7803-0510-8
  • Type

    conf

  • DOI
    10.1109/MWSCAS.1992.271071
  • Filename
    271071