• DocumentCode
    1749410
  • Title

    Activity detection in unknown noise environment

  • Author

    Fishler, Eran ; Messer, Hagit

  • Author_Institution
    Dept. of Electr. Eng.-Syst., Tel Aviv Univ., Israel
  • Volume
    5
  • fYear
    2001
  • fDate
    2001
  • Firstpage
    3185
  • Abstract
    In many applications there exists an array of cells (or bins), each containing either an activity (signal) plus noise, or noise only. A common problem is to identify the active bins, assuming that the noise level in the array is unknown. In this paper we present a novel approach for solving this problem. The approach is based on two steps. In the first, we estimate the noise level and in the second we perform a sequential test to decide, for each bin, whether it is active or not. We show that the proposed algorithm collapses to well known special cases. The performance of the proposed algorithm is analyzed analytically and is demonstrated via simulation results
  • Keywords
    iterative methods; maximum likelihood detection; maximum likelihood estimation; noise; active bins; activity detection; array; maximum likelihood; sequential test; unknown noise environment; Additive noise; Analytical models; Image denoising; Noise level; Noise measurement; Performance analysis; Performance evaluation; Sequential analysis; Wavelet transforms; Working environment noise;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech, and Signal Processing, 2001. Proceedings. (ICASSP '01). 2001 IEEE International Conference on
  • Conference_Location
    Salt Lake City, UT
  • ISSN
    1520-6149
  • Print_ISBN
    0-7803-7041-4
  • Type

    conf

  • DOI
    10.1109/ICASSP.2001.940335
  • Filename
    940335