TY - GEN
T1 - Greedy Orthogonal Matching Pursuit algorithm for sparse signal recovery in compressive sensing
AU - Li, Jia
AU - Wu, Zhaojun
AU - Feng, Hongqi
AU - Wang, Qiang
AU - Liu, Yipeng
PY - 2014
Y1 - 2014
N2 - The sparse signal recovery problem has been the subject of extensive research in several different communities. Tractable recovery algorithm is a crucial and fundamental theme of compressive sensing (CS), which has drawn significant interests in the last few years. In this paper, we firstly analyze the iterative residual in Orthogonal Matching Pursuit (OMP) algorithm. Secondly, a greedier algorithm is introduced, which is called Greedy OMP (GOMP) algorithm. This algorithm iteratively identifies more than one atoms using greedy atom identification, and then discards some atoms, which are of high similarity with the optimal atom. Compared with OMP algorithm, the experiments conducted on Gaussian and Zero-one sparse signal demonstrate that the proposed GOMP algorithm can provide better recovery performance. Finally, we experimentally investigate the effect of greedy constant in GOMP upon the recovery performance.
AB - The sparse signal recovery problem has been the subject of extensive research in several different communities. Tractable recovery algorithm is a crucial and fundamental theme of compressive sensing (CS), which has drawn significant interests in the last few years. In this paper, we firstly analyze the iterative residual in Orthogonal Matching Pursuit (OMP) algorithm. Secondly, a greedier algorithm is introduced, which is called Greedy OMP (GOMP) algorithm. This algorithm iteratively identifies more than one atoms using greedy atom identification, and then discards some atoms, which are of high similarity with the optimal atom. Compared with OMP algorithm, the experiments conducted on Gaussian and Zero-one sparse signal demonstrate that the proposed GOMP algorithm can provide better recovery performance. Finally, we experimentally investigate the effect of greedy constant in GOMP upon the recovery performance.
KW - Compressive sensing
KW - measurement matrix
KW - orthogonal matching pursuit
KW - sparse signal reconstruction
UR - https://www.scopus.com/pages/publications/84905682568
U2 - 10.1109/I2MTC.2014.6860967
DO - 10.1109/I2MTC.2014.6860967
M3 - 会议稿件
AN - SCOPUS:84905682568
SN - 9781467363853
T3 - Conference Record - IEEE Instrumentation and Measurement Technology Conference
SP - 1355
EP - 1358
BT - 2014 IEEE International Instrumentation and Measurement Technology Conference
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2014 IEEE International Instrumentation and Measurement Technology Conference: Instrumentation and Measurement for Sustainable Development, I2MTC 2014
Y2 - 12 May 2014 through 15 May 2014
ER -