• DocumentCode
    2226513
  • Title

    Monte Carlo analysis of resistive networks without a priori probability distributions

  • Author

    Barmish, B. Ross ; Kettani, Houssain

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Wisconsin Univ., Madison, WI, USA
  • Volume
    3
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    263
  • Abstract
    In this paper, we formulate and solve a new type of Monte Carlo problem for a resistive network. Given lower and upper bounds on the value of each resistor but no probability distribution, we consider the problem of finding the expected value for a designated gain. In view of the fact that no a priori probability distributions for the uncertain resistors are assumed, a certain type “distributional robustness” is sought. To this end, a new paradigm from the robustness literature is particularized to circuits and results are provided in this context. Some of the performance bounds obtained via this new approach differ considerably from those which result from a more conventional Monte Carlo simulation
  • Keywords
    Monte Carlo methods; linear network analysis; lumped parameter networks; passive networks; Monte Carlo analysis; designated gain; distributional robustness; expected value; resistive networks; uncertain resistors; Circuits; Monte Carlo methods; Probability density function; Probability distribution; Resistors; Robustness; Uncertainty; Upper bound; Voltage; Writing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Circuits and Systems, 2000. Proceedings. ISCAS 2000 Geneva. The 2000 IEEE International Symposium on
  • Conference_Location
    Geneva
  • Print_ISBN
    0-7803-5482-6
  • Type

    conf

  • DOI
    10.1109/ISCAS.2000.856047
  • Filename
    856047