• DocumentCode
    2515269
  • Title

    Neural recognition of diagnostic test data transforms

  • Author

    Scully, John K.

  • Author_Institution
    JKS Syst. Ltd., Westlake Village, CA, USA
  • fYear
    1994
  • fDate
    20-22 Sep 1994
  • Firstpage
    433
  • Lastpage
    437
  • Abstract
    By extending the concept of fault signatures on the primary outputs of the UUT to include the multiple parameters required of mixed signal testing, a fault dictionary approach to mixed signal UUT diagnostics can be developed. Transforms of fault signature ensemble information, as opposed to transforms of the time varying test signals themselves, can then be used as inputs to a neural net, the outputs of which are available to enhance conventional, fault dictionary processing of the original fault signature information
  • Keywords
    automatic test equipment; fault diagnosis; integrated circuit testing; mixed analogue-digital integrated circuits; neural nets; pattern recognition; transforms; UUT; diagnostic test data transforms; fault dictionary approach; fault dictionary processing; fault signature information; fault signatures; mixed signal UUT diagnostics; mixed signal testing; multiple parameters; neural net; neural recognition; primary outputs; time varying test signals; Automatic programming; Automatic testing; Data structures; Dictionaries; Fault detection; Humans; Manuals; Neural networks; Sequential analysis; Signal processing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    AUTOTESTCON '94. IEEE Systems Readiness Technology Conference. 'Cost Effective Support Into the Next Century', Conference Proceedings.
  • Conference_Location
    Anaheim, CA
  • Print_ISBN
    0-7803-1910-9
  • Type

    conf

  • DOI
    10.1109/AUTEST.1994.381587
  • Filename
    381587