• DocumentCode
    247787
  • Title

    Neural network training schemes for antenna optimization

  • Author

    Linh Ho Manh ; Grimaccia, F. ; Mussetta, M. ; Zich, Riccardo E.

  • Author_Institution
    Dipt. di Energia, Politec. di Milano, Milan, Italy
  • fYear
    2014
  • fDate
    6-11 July 2014
  • Firstpage
    1948
  • Lastpage
    1949
  • Abstract
    Thanks to the advantage of low profile and low cost, microstrip ring antenna design has been an interesting and challenging issue in modern engineering society. The trade-off among all the degrees of freedom becomes quite complex and direct antenna synthesis by full-wave analysis are often not applicable. In optimization scheme, the associated cost function by computational approach is always expensive and time-consuming. Artificial Neural Network (ANN) has been exploit as a modeling methodology in Electromagnetic field in recent years. In this article, a new approach with the aim of boosting “online-trading information” between the global optimizer and ANN surrogate model will be discussed.
  • Keywords
    electrical engineering computing; microstrip antennas; neural nets; ANN surrogate model; antenna optimization scheme; artificial neural network; degrees of freedom; direct antenna synthesis; electromagnetic field modeling methodology; full-wave analysis; global optimizer; low cost microstrip ring antenna design; low profile microstrip ring antenna design; neural network training schemes; online-trading information; Artificial neural networks; Biological neural networks; Computational modeling; Microstrip antennas; Optimization; Training;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Antennas and Propagation Society International Symposium (APSURSI), 2014 IEEE
  • Conference_Location
    Memphis, TN
  • ISSN
    1522-3965
  • Print_ISBN
    978-1-4799-3538-3
  • Type

    conf

  • DOI
    10.1109/APS.2014.6905301
  • Filename
    6905301