• DocumentCode
    1460296
  • Title

    Design and optimization of CPW circuits using EM-ANN models for CPW components

  • Author

    Watson, Paul M. ; Gupta, Kuldip C.

  • Author_Institution
    Colorado Univ., Boulder, CO, USA
  • Volume
    45
  • Issue
    12
  • fYear
    1997
  • fDate
    12/1/1997 12:00:00 AM
  • Firstpage
    2515
  • Lastpage
    2523
  • Abstract
    Accurate and efficient electromagnetically trained artificial neural-network (EM-ANN) models have been developed for coplanar waveguide (CPW) circuit components. Modeled components include: CPW transmission lines (frequency dependent Z0 and εre ), 90° bends, short-circuit stubs, open-circuit stubs, step-in-width discontinuities, and symmetric T-junctions. These models allow for circuit design, simulation, and optimization within a commercial microwave circuit simulator environment, while providing the accuracy of electromagnetic (EM) simulation. Design and optimization of a CPW folded double-stub filter and a 50-Ω 3-dB power divider circuit using the developed CPW EM-ANN models are demonstrated
  • Keywords
    MMIC; circuit CAD; circuit analysis computing; circuit optimisation; coplanar waveguides; integrated circuit design; neural nets; power dividers; waveguide discontinuities; waveguide filters; 50 ohm; CPW bends; CPW circuits; CPW components; CPW transmission lines; EM-ANN models; circuit design; electromagnetically trained artificial neural-network; folded double-stub filter; microwave circuit simulator environment; open-circuit stubs; optimization; power divider circuit; short-circuit stubs; simulation; step-in-width discontinuities; symmetric T-junctions; Circuit simulation; Coplanar transmission lines; Coplanar waveguides; Design optimization; Distributed parameter circuits; Electromagnetic modeling; Electromagnetic waveguides; Frequency dependence; Power transmission lines; Waveguide components;
  • fLanguage
    English
  • Journal_Title
    Microwave Theory and Techniques, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9480
  • Type

    jour

  • DOI
    10.1109/22.643868
  • Filename
    643868