• DocumentCode
    775727
  • Title

    A hierarchical network approach to symbolic analysis of large-scale networks

  • Author

    Hassoun, Marwan M. ; Lin, Pen-Min

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Iowa State Univ., Ames, IA, USA
  • Volume
    42
  • Issue
    4
  • fYear
    1995
  • fDate
    4/1/1995 12:00:00 AM
  • Firstpage
    201
  • Lastpage
    211
  • Abstract
    A hierarchical approach to the problem of symbolic circuit analysis of large-scale circuits is presented in this paper. The methodology has been implemented in a computer program called SCAPP (Symbolic Circuit Analysis Program with Partitioning). The method solves the problem by utilizing a hierarchical network approach and the sequence of expressions concept rather than a topological approach and the single expression idea which have dominated symbolic analysis in the past. The result is a linear growth (for real circuits) in the number of terms in the symbolic solutions for the network approach versus the exponential growth exhibited by traditional methods. The analysis methodology uses a Reduced Modified Nodal Analysis (RMNA) technique that allows the characterization of symbolic networks in terms of only a small subset of the network variables (external variables). The analysis algorithm is most efficient when network partitioning is used. Partitioning results in a reduction in the number of terms in the symbolic solutions
  • Keywords
    circuit analysis computing; network topology; symbol manipulation; SCAPP; computer program; hierarchical network approach; large-scale networks; network partitioning; reduced modified nodal analysis; symbolic analysis; Admittance; Algorithm design and analysis; Analytical models; Circuit analysis; Circuit analysis computing; Circuit simulation; Frequency; Large-scale systems; Partitioning algorithms; Transfer functions;
  • fLanguage
    English
  • Journal_Title
    Circuits and Systems I: Fundamental Theory and Applications, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1057-7122
  • Type

    jour

  • DOI
    10.1109/81.382473
  • Filename
    382473