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
Link To Document :
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