• DocumentCode
    1145459
  • Title

    Universal simulation distributions

  • Author

    Bucklew, James A. ; Nitinawarat, Sirin ; Wierer, Jay

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Univ. of Wisconsin-Madison, Madison, WI, USA
  • Volume
    50
  • Issue
    11
  • fYear
    2004
  • Firstpage
    2674
  • Lastpage
    2685
  • Abstract
    In this paper, we present a new class of importance sampling simulation distributions, the universal distributions. We show that these distributions are universally efficient in the sense that they depend only on a single scalar parameter regardless of the dimensionality of the underlying system or of the error sets to be simulated.
  • Keywords
    importance sampling; probability; Monte Carlo simulation; importance sampling; large deviation theory; scalar parameter; universal simulation distributions; Books; Communication systems; Discrete event simulation; H infinity control; Monte Carlo methods; Probability density function; Random number generation; Random variables; Sampling methods; Signal detection; Importance sampling; Monte Carlo simulation; large deviation theory;
  • fLanguage
    English
  • Journal_Title
    Information Theory, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9448
  • Type

    jour

  • DOI
    10.1109/TIT.2004.836875
  • Filename
    1347355
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1145459