• DocumentCode
    2824615
  • Title

    A large-signal neural network model for the dual gate MESFET

  • Author

    Abdeen, M. ; Bennett, J. ; Yagoub, M.C.E.

  • Author_Institution
    SITE, Ottawa Univ., Ont., Canada
  • Volume
    3
  • fYear
    2003
  • fDate
    27-30 Dec. 2003
  • Firstpage
    1323
  • Abstract
    The paper presents for the first time a large-signal neural model of the dual-gate MESFET. The neural model is a five-layer perceptrons (MLP5) with one input, one output, and three hidden layers. The model is based on pulsed I-V measurements to better represent the RF device behavior and to neutralize the effect of channel heating on the model accuracy. The neural model is shown to be in an excellent agreement with measurements (with an error less than 1%).
  • Keywords
    Schottky gate field effect transistors; circuit CAD; perceptrons; RF device; channel heating; dual gate MESFET; five-layer perceptrons; neural network model; pulsed I-V measurements; Current measurement; Dispersion; Electrical resistance measurement; FETs; MESFETs; Microwave devices; Neural networks; Pulse measurements; Radio frequency; Transconductance;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Circuits and Systems, 2003 IEEE 46th Midwest Symposium on
  • ISSN
    1548-3746
  • Print_ISBN
    0-7803-8294-3
  • Type

    conf

  • DOI
    10.1109/MWSCAS.2003.1562539
  • Filename
    1562539