TY - JOUR ID - 1882 TI - SPARSE SIGNAL RECONSTRUCTION FROM COMPRESSED SENSING MEASUREMENTS BASED ON DETECTION THEORY JO - Iranian Journal of Science and Technology Transactions of Electrical Engineering JA - IJSTE LA - en SN - 2228-6179 Y1 - 2013 PY - 2013 VL - 37 IS - 2 SP - 101 EP - 120 KW - Sparse signal reconstruction KW - compressed sensing KW - detection theory KW - composite multiple hypothesis test DO - 10.22099/ijste.2013.1882 N2 - The problem of sparse signal reconstruction from the well-known Compressed Sensingmeasurement is considered in this paper. The measured signal is assumed to be corrupted withadditive white Gaussian noise with zero mean and known variance. Based on detection theory, twoiterative algorithms are developed for detection and estimation of nonzero elements of sparsesignal. The principle of the proposed methods is based on applying composite multiple hypothesistest to the underlying problem at each iteration. Simulation results show the satisfactoryperformance of the proposed algorithms in sparse signal recovery. The proposed approach has thepotential of being applied to other models for noise and signal. UR - https://ijste.shirazu.ac.ir/article_1882.html L1 - https://ijste.shirazu.ac.ir/article_1882_61843f048972b1f9217e6dc870dc5cf4.pdf ER -