• DocumentCode
    2801912
  • Title

    Parameter optimization for importance sampling in encoded systems

  • Author

    Melo, Hallyson L M ; Gurjão, Edmar C. ; Albert, Bruno B. ; De Assis, Francisco M.

  • Author_Institution
    Fed. Univ. of Campina Grande, Campina Grande
  • fYear
    2006
  • fDate
    3-6 Sept. 2006
  • Firstpage
    95
  • Lastpage
    99
  • Abstract
    In this paper we present a new methodology based on the stochastic gradient descent to optimizing parameters of the biased distribution along importance sampling simulations. A particular aspect of the new technique is that of use of multiple parameters for the simulation of each codeword. An example of application estimating the performance of a encoded system is given.
  • Keywords
    encoding; gradient methods; importance sampling; optimisation; stochastic processes; biased distribution; codeword; encoded systems; importance sampling simulations; parameter optimization; stochastic gradient descent; Bit error rate; Computational modeling; Decoding; Discrete event simulation; Distribution functions; Error probability; Monte Carlo methods; Optimization methods; Performance analysis; Stochastic systems; Importance Sampling; Optimization; Simulation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Telecommunications Symposium, 2006 International
  • Conference_Location
    Fortaleza, Ceara
  • Print_ISBN
    978-85-89748-04-9
  • Electronic_ISBN
    978-85-89748-04-9
  • Type

    conf

  • DOI
    10.1109/ITS.2006.4433249
  • Filename
    4433249
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2801912