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Sparse Signal Recovery via Optimized Orthogonal Matching Pursuit

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5 Author(s)
Zhilin Li ; Sch. of Electron. & Inf. Eng., Beijing Jiaotong Univ., Beijing, China ; Houjin Chen ; Chang Yao ; Jupeng Li
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The recovery algorithm is a crucial issue of the compressed sensing (CS). This paper presents a greedy algorithm called optimized orthogonal matching pursuit (OOMP) for sparse signal recovery. The OOMP algorithm improves the orthogonal matching pursuit (OMP) algorithm via providing the projection onto the subspace generated by the selected measurements and minimizing the corresponding residual error at each iteration. Compared with the OMP algorithm, the simulation results show that the proposed algorithm provides a better approximation of a given signal and reduces measurements needed to recover the signal accurately.

Published in:

Image and Signal Processing, 2009. CISP '09. 2nd International Congress on

Date of Conference:

17-19 Oct. 2009