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. (1392). SPARSE SIGNAL RECONSTRUCTION FROM COMPRESSED SENSING MEASUREMENTS BASED ON DETECTION THEORY. , 37(2), 101-120. doi: 10.22099/ijste.2013.1882
. "SPARSE SIGNAL RECONSTRUCTION FROM COMPRESSED SENSING MEASUREMENTS BASED ON DETECTION THEORY". , 37, 2, 1392, 101-120. doi: 10.22099/ijste.2013.1882
. (1392). 'SPARSE SIGNAL RECONSTRUCTION FROM COMPRESSED SENSING MEASUREMENTS BASED ON DETECTION THEORY', , 37(2), pp. 101-120. doi: 10.22099/ijste.2013.1882
. SPARSE SIGNAL RECONSTRUCTION FROM COMPRESSED SENSING MEASUREMENTS BASED ON DETECTION THEORY. , 1392; 37(2): 101-120. doi: 10.22099/ijste.2013.1882

SPARSE SIGNAL RECONSTRUCTION FROM COMPRESSED SENSING MEASUREMENTS BASED ON DETECTION THEORY

Iranian Journal of Science and Technology Transactions of Electrical Engineering
شناسنامه علمی شماره، دوره 37، شماره 2، اسفند 2013، صفحه 101-120    اصل مقاله (238.2 K)
شناسه دیجیتال (DOI): 10.22099/ijste.2013.1882
چکیده
The problem of sparse signal reconstruction from the well-known Compressed Sensing
measurement is considered in this paper. The measured signal is assumed to be corrupted with
additive white Gaussian noise with zero mean and known variance. Based on detection theory, two
iterative algorithms are developed for detection and estimation of nonzero elements of sparse
signal. The principle of the proposed methods is based on applying composite multiple hypothesis
test to the underlying problem at each iteration. Simulation results show the satisfactory
performance of the proposed algorithms in sparse signal recovery. The proposed approach has the
potential of being applied to other models for noise and signal.
کلیدواژه‌ها
Sparse signal reconstruction؛ compressed sensing؛ detection theory؛ composite multiple hypothesis test
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