• DocumentCode
    1895415
  • Title

    ANN characterization of printed reflectarray elements

  • Author

    Mussetta, M. ; Pirinoli, P. ; Zich, R.E. ; Orefice, M.

  • Author_Institution
    Dipt. Elettron., Politec. di Torino, Torino, Italy
  • fYear
    2010
  • fDate
    11-17 July 2010
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    The design of printed reflectarray antennas (RAs) could be quite complex and computationally expensive, since the need of providing high performances and satisfying requirements that could be also in contrast each other could require the use of a large number of re-radiating advanced element configurations. A possible strategy for the RA design could be therefore of carrying it out adopting an evolutionary optimization tool. In this work, an artificial neural network (ANN) model of the RA single element is presented as convenient interface between antenna design and global optimization algorithms. In order to prove the effectiveness of the model, it will be used in the design of a dual-band dual-layer reflectarray.
  • Keywords
    evolutionary computation; microstrip antenna arrays; neural nets; reflector antennas; ANN characterization; artificial neural network; dual-band dual-layer reflectarray; evolutionary optimization tool; global optimization algorithm; printed reflectarray element; Antennas; Artificial neural networks; Computational modeling; Numerical models; Optimization; Reflection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Antennas and Propagation Society International Symposium (APSURSI), 2010 IEEE
  • Conference_Location
    Toronto, ON
  • ISSN
    1522-3965
  • Print_ISBN
    978-1-4244-4967-5
  • Type

    conf

  • DOI
    10.1109/APS.2010.5561971
  • Filename
    5561971