• DocumentCode
    2059547
  • Title

    Hierarchical approach to diagnosis using ANNs

  • Author

    Stosovic, Miona Andrejevic ; Litovski, Vanco

  • Author_Institution
    Dept. of Electron., Univ. of Nis, Nis
  • fYear
    2008
  • fDate
    11-14 May 2008
  • Firstpage
    395
  • Lastpage
    398
  • Abstract
    Feed-forward artificial neural networks (ANNs) have been applied to defects diagnosis in an electronic circuit, and also a hierarchical approach is introduced in diagnosis procedure. The approach is presented on an example of a mixed-mode circuit that can represent every complex circuit. A voting system is created in order to distinguish which ANN´s output is to be accepted as the final diagnostic statement. Three examples illustrate this approach, so validating the effectiveness of this procedure.
  • Keywords
    electronic engineering computing; feedforward neural nets; ANN duagbisus; complex circuits; electronic circuit defect diagnosis; feedforward artificial neural networks; hierarchical approach; mixed-mode circuit; voting system; Circuit faults; Circuit testing; Design engineering; Dictionaries; Electronic circuits; Fault diagnosis; Production; Signal processing; System testing; Voting;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Microelectronics, 2008. MIEL 2008. 26th International Conference on
  • Conference_Location
    Nis
  • Print_ISBN
    978-1-4244-1881-7
  • Electronic_ISBN
    978-1-4244-1882-4
  • Type

    conf

  • DOI
    10.1109/ICMEL.2008.4559304
  • Filename
    4559304