• DocumentCode
    2054942
  • Title

    Asymptotic robust Neyman-Pearson hypothesis testing based on moment classes

  • Author

    Pandit, C. ; Meyn, S. ; Veeravalli, V.

  • Author_Institution
    Dept. of ECE & CSL, UIUC, Urbana, IL, USA
  • fYear
    2004
  • fDate
    27 June-2 July 2004
  • Firstpage
    220
  • Abstract
    A robust hypothesis testing framework is introduced in which candidate hypotheses are characterized by moment classes. It is shown that there exists a test sequence that is asymptotically optimal in the min-max sense, and that it is expressed as a comparison of a log-linear combination of the constraint functions to a predetermined threshold.
  • Keywords
    binary sequences; minimax techniques; numerical analysis; asymptotic robust Neyman-Pearson hypothesis testing; log-linear combination; min-max sense; moment class; test sequence; Constraint optimization; Probability distribution; Robustness; Testing; Uncertainty;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Theory, 2004. ISIT 2004. Proceedings. International Symposium on
  • Print_ISBN
    0-7803-8280-3
  • Type

    conf

  • DOI
    10.1109/ISIT.2004.1365255
  • Filename
    1365255
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2054942