• DocumentCode
    1964330
  • Title

    Microwave Devices and Antennas Modelling by Support Vector Regression Machines

  • Author

    Angiulli, G. ; Cacciola, M. ; Versaci, M.

  • Author_Institution
    DIMET, Mediterranea Univ., Calabria
  • fYear
    0
  • fDate
    0-0 0
  • Firstpage
    302
  • Lastpage
    302
  • Abstract
    Artificial neural networks have been employed as a fast tool for microwave device modelling. Support vector machines developed by Vapnik are gaining popularity due to many attractive features capable to overcome the limitations connected to ANNs. In this work, we discuss the use of support vector regression machines for microwave devices and antenna modelling
  • Keywords
    electrical engineering computing; microwave antennas; neural nets; support vector machines; antennas; artificial neural networks; microwave devices; support vector regression machines; Artificial neural networks; Biomedical engineering; Biomedical signal processing; Computational electromagnetics; Lab-on-a-chip; Microwave antennas; Microwave devices; Performance analysis; Support vector machines; Wireless communication;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electromagnetic Field Computation, 2006 12th Biennial IEEE Conference on
  • Conference_Location
    Miami, FL
  • Print_ISBN
    1-4244-0320-0
  • Type

    conf

  • DOI
    10.1109/CEFC-06.2006.1633092
  • Filename
    1633092
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1964330