• DocumentCode
    2734232
  • Title

    HOS-based noise models for signal detection optimization in non-Gaussian environments

  • Author

    Tesei, Anna ; Regazzoni, C.S.

  • Author_Institution
    DIBE, Genoa Univ.
  • fYear
    1995
  • fDate
    17-22 Sep 1995
  • Firstpage
    296
  • Abstract
    Two probability density function (pdf) models suitable for describing non-Gaussian i.i.d. noise are introduced. The models are used in the design of a locally optimum detector test for detecting weak signals in real non-Gaussian noise. Results obtained in the context of an underwater acoustic application are encouraging
  • Keywords
    acoustic noise; acoustic signal detection; higher order statistics; optimisation; random noise; signal detection; underwater sound; higher order statistics; locally optimum detector test; noise models; non-Gaussian i.i.d. noise; probability density function models; signal detection optimization; underwater acoustic application; weak signals; Higher order statistics; Signal to noise ratio; Working environment noise;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Theory, 1995. Proceedings., 1995 IEEE International Symposium on
  • Conference_Location
    Whistler, BC
  • Print_ISBN
    0-7803-2453-6
  • Type

    conf

  • DOI
    10.1109/ISIT.1995.535811
  • Filename
    535811
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2734232