• DocumentCode
    2137256
  • Title

    Parameterized compact model synthesis based on sonnet electromagnetic analysis data

  • Author

    Rautio, James C.

  • Author_Institution
    Sonnet Software, Inc., Syracuse, NY, USA
  • fYear
    2012
  • fDate
    8-14 July 2012
  • Firstpage
    1
  • Lastpage
    2
  • Abstract
    Sonnet® can synthesize compact lumped models based on electromagnetic analysis results. Synthesis equations have been derived for 662 two-terminal lumped RLC networks. For a given electromagnetic analysis derived impedance or admittance frequency characteristic, each of the 662 two-terminal networks is synthesized based on data at only a few frequencies. Then, of all the synthesized networks, the network which best matches the frequency characteristic at non-synthesis frequencies is selected. This means that for a 2-port Pi-network, which uses three two-terminal networks, the synthesis solution space includes over 300 million possible topologies. In addition, the resulting compact lumped models can be parameterized. A parameterized lumped model for the input impedance of a planer microstrip dipole illustrates the technique.
  • Keywords
    computational electromagnetics; data analysis; electric admittance; electric impedance; electronic engineering computing; lumped parameter networks; two-port networks; 2-port Pi-network; Sonnet electromagnetic analysis data; admittance frequency characteristic; impedance; microstrip dipole; nonsynthesis frequency; parameterized compact lumped model; synthesis equation; synthesized network; two-terminal lumped RLC network; Analytical models; Electromagnetic analysis; Equations; Frequency synthesizers; Impedance; Integrated circuit modeling; Mathematical model;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Antennas and Propagation Society International Symposium (APSURSI), 2012 IEEE
  • Conference_Location
    Chicago, IL
  • ISSN
    1522-3965
  • Print_ISBN
    978-1-4673-0461-0
  • Type

    conf

  • DOI
    10.1109/APS.2012.6348423
  • Filename
    6348423