• DocumentCode
    2217744
  • Title

    A New Formulation of Dynamic Neural Network for Modeling of Nonlinear RF/Microwave Circuits

  • Author

    Deo, Makarand ; Xu, Jianjun ; Zhang, Q.J.

  • Author_Institution
    Dept. of Electronics, Carleton University, 1125 Colonel By Dr., Ottawa, Canada K1S 5B6. mdeo@doe.carleton.ca
  • fYear
    2003
  • fDate
    Oct. 2003
  • Firstpage
    1019
  • Lastpage
    1022
  • Abstract
    In this paper, we propose a new formulation of dynamic neural network (DNN) for modeling of nonlinear RF/microwave devices or circuits in continuous time domain. The proposed model can be trained directly from input-output large-signal data irrespective of internal details of the circuit. The proposed approach maintains the accuracy even in presence of measurement noise in training data. A circuit representation of the proposed model is introduced in order to incorporate it into circuit simulators for high-level design. Examples of dynamic modeling of FET amplifier operating at high frequencies are presented.
  • Keywords
    Artificial neural networks; Circuit noise; Circuit simulation; Microwave circuits; Microwave devices; Microwave theory and techniques; Neural networks; Radio frequency; Recurrent neural networks; Training data;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Microwave Conference, 2003 33rd European
  • Conference_Location
    Munich, Germany
  • Print_ISBN
    1-58053-834-7
  • Type

    conf

  • DOI
    10.1109/EUMA.2003.340832
  • Filename
    4143193