• DocumentCode
    3024429
  • Title

    Accurate modeling of low actuation voltage RFMEMS switches using artificial neural networks

  • Author

    Pak, Amin ; Mafinejad, Yasser ; Kouzani, Abbas ; Nabovati, Hooman ; Mafinezhad, Khalil

  • Author_Institution
    Sadjad Inst. for Higher Educ., Mashhad, Iran
  • fYear
    2012
  • fDate
    20-23 May 2012
  • Firstpage
    3282
  • Lastpage
    3284
  • Abstract
    This paper presents a fast and accurate method for extracting the scattering parameters of a RF MEMS switch by using its essential parameters. A neural network is developed for parametric modeling of the switch. The essential parameters of the switch are analyzed in terms of its return loss and isolation with variation of its geometrical component values. Simulation results show that the proposed approach can be used to accurately model the RF characteristics of RF-MEMS switches. The results show good agreement between the neural network prediction and electromagnetic simulations.
  • Keywords
    microswitches; neural nets; radiofrequency integrated circuits; RF-MEMS switches; artificial neural networks; electromagnetic simulations; geometrical component values; low actuation voltage; neural network prediction; parameter extraction; scattering parameter; Artificial neural networks; Micromechanical devices; Microswitches; Microwave circuits; Radio frequency;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Circuits and Systems (ISCAS), 2012 IEEE International Symposium on
  • Conference_Location
    Seoul
  • ISSN
    0271-4302
  • Print_ISBN
    978-1-4673-0218-0
  • Type

    conf

  • DOI
    10.1109/ISCAS.2012.6272026
  • Filename
    6272026