• DocumentCode
    1722759
  • Title

    Neural network modelling of electromagnetic field problems

  • Author

    Ratner, I. ; Ali, H.O. ; Petriu, E.M. ; Eatherley, G.

  • Author_Institution
    Ottawa Univ., Ont., Canada
  • fYear
    1996
  • Firstpage
    387
  • Lastpage
    391
  • Abstract
    This paper discusses the application of neural network (NN) technique in the modelling of a typical electromagnetic (EM) field problem consisting of a coaxially-driven dielectric-ring resonator antenna. The NN takes into consideration the geometrical and material parameters of the EM model, and the reflection coefficient values for different frequencies in the bandwidth of interest. The NN is trained off-line using the training sets generated by the finite element method. Once an acceptable NN model is found by simulation it can be implemented in hardware in order to provide the real time behaviour requested for further integration in an EM-CAD tool
  • Keywords
    Maxwell equations; antenna theory; dielectric resonators; electromagnetic fields; feedforward neural nets; finite element analysis; modelling; EM CAD tool; EM field model; dielectric-ring resonator antenna; electromagnetic field; feedforward neural network; finite element method; neural network modelling; reflection coefficient; Bandwidth; Coaxial components; Dielectric materials; Dielectric resonator antennas; Electromagnetic fields; Electromagnetic modeling; Electromagnetic reflection; Frequency; Neural networks; Solid modeling;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks for Identification, Control, Robotics, and Signal/Image Processing, 1996. Proceedings., International Workshop on
  • Conference_Location
    Venice
  • Print_ISBN
    0-8186-7456-3
  • Type

    conf

  • DOI
    10.1109/NICRSP.1996.542782
  • Filename
    542782