Ninth International Conference On Advances In Computing, Control And Networking - ACCN 2019
Author(s) : LING-HUA CHANG, WEN SEN LIU, JIA FU WU
Orthogonal matching pursuit (OMP) is a commonly used algorithm in compressed sensing (CS) for estimating a sparse vector/signal x from linear measurements y m , where m n . There are two generally stopping criteria adopted in the iterative OMP. One, assuming the number of nonzero entries of the sparse vector x is known, stop the algorithm after exactly K iterations. The other halt the pursuit if the strength of the residual is smaller than some threshold. These two criteria respectively rely on certain knowledge about the signal and the environment/noise. We propose a normalized residual strength based stopping criterion, which can be employed without the information mentioned above. Numerical results show that under some circumstances, the proposed criterion leads to a smaller normalized signal reconstruction error as compared to that achieved by OMP with exact K iterations and the conventional residual strength based stopping criterion.