• DocumentCode
    3087903
  • Title

    Radial Basis Function Neural Networks for Filling the MoM Impedance Matrix

  • Author

    Zainud-Deen, S.H. ; Ibrahim, I.I. ; Ibrahem, Sabry M M ; Hassan, A.S.

  • Author_Institution
    Fac. of Electron. Eng., Menoufia Univ.
  • Volume
    0
  • fYear
    2006
  • fDate
    14-16 March 2006
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    In this paper radial basis function neural network (RBF-NN) used for filling the method of moments (MoM) impedance matrix of several configuration of wire antennas. Four radial basis function neural networks (RBF-NNs) are trained to calculate the impedances of two elements consist of four monopoles. The mutual impedance between the two elements is the sum of outputs of the four RBF-NNs. The RBF-NN model is applied to the analysis of the straight dipole, two element array, circular array, wire-grid corner reflector, square loop, and square spiral antenna
  • Keywords
    antenna radiation patterns; electric impedance; electrical engineering computing; impedance matrix; method of moments; monopole antenna arrays; radial basis function networks; wire antennas; MoM impedance matrix; RBF-NN; method of moment; mutual impedance; radial basis function neural network; wire antenna; Antenna arrays; Dipole antennas; Equations; Filling; Frequency; Impedance; Radial basis function networks; Shape; Spirals; Transmission line matrix methods;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Radio Science Conference, 2006. NRSC 2006. Proceedings of the Twenty Third National
  • Conference_Location
    Menoufiya
  • Print_ISBN
    977-5031-84-2
  • Electronic_ISBN
    977-5031-84-2
  • Type

    conf

  • DOI
    10.1109/NRSC.2006.386319
  • Filename
    4275116