• DocumentCode
    285631
  • Title

    Sensitivity analysis of large linear networks using symbolic programs

  • Author

    Lin, P.M.

  • Author_Institution
    Purdue Univ., West Lafayette, IN, USA
  • Volume
    3
  • fYear
    1992
  • fDate
    10-13 May 1992
  • Firstpage
    1145
  • Abstract
    Partial derivatives of a network function H(x) with respect to the parameters x=(x1, x2,,,,xn) are useful in the design of linear networks by optimization and in tolerance analysis. Existing methods for calculating these derivatives include the sensitivity network method, the adjoint network method, and the symbolic network function method. In recent years, several new methods have been developed for symbolic analysis of large linear networks. The new methods express the symbolic answer in the form of a sequence of expressions. The author investigates the calculation of the derivatives based on the sequence of expressions. Two methods are presented. The first method derives another sequence of expressions for each sensitivity function. The second method utilizes a 3-point formula to determine the coefficients in the bilinear function from which the sensitivity function is calculated
  • Keywords
    active networks; ladder networks; linear network analysis; network parameters; passive networks; sensitivity analysis; symbol manipulation; active network; bilinear function; ladder network; large linear networks; network function; optimization; passive filter; sensitivity function; symbolic programs; tolerance analysis; Circuit analysis; Computer networks; Design optimization; Frequency; Impedance; Laplace equations; Sensitivity analysis; Steady-state; Tolerance analysis; Transfer functions;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Circuits and Systems, 1992. ISCAS '92. Proceedings., 1992 IEEE International Symposium on
  • Conference_Location
    San Diego, CA
  • Print_ISBN
    0-7803-0593-0
  • Type

    conf

  • DOI
    10.1109/ISCAS.1992.230324
  • Filename
    230324