• DocumentCode
    993037
  • Title

    The analysis of the faulty behavior of synchronous neural networks

  • Author

    Belfore, Lee A., II ; Johnson, Barry W.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Marquette Univ., Milwaukee, WI, USA
  • Volume
    40
  • Issue
    12
  • fYear
    1991
  • fDate
    12/1/1991 12:00:00 AM
  • Firstpage
    1424
  • Lastpage
    1429
  • Abstract
    A means for analyzing the faulty behavior of neural networks is presented. Using an analogy between statistical physics and neural networks, a method for assessing the performance of a synchronous neural network model in the presence of faults is developed. Analytical predictions are computed using the statistical physics analogy and compared with the simulated behavior for two neuron models. An example of the analytical technique applied to an autoassociative memory is described
  • Keywords
    content-addressable storage; fault tolerant computing; neural nets; analytical predictions; faulty behavior; performance assessment; simulated behavior; statistical physics; synchronous neural networks; Biological system modeling; Computer networks; Computer vision; Fault tolerance; Image segmentation; Labeling; Layout; Neural networks; Physics; Speech processing;
  • fLanguage
    English
  • Journal_Title
    Computers, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9340
  • Type

    jour

  • DOI
    10.1109/12.106228
  • Filename
    106228
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=993037