TY - GEN
T1 - Sparse signal recovery via multipath matching pursuit
AU - Kwon, Suhyuk
AU - Wang, Jian
AU - Shim, Byonghyo
PY - 2013
Y1 - 2013
N2 - In this paper, we propose a sparse recovery algorithm, termed multiple path matching pursuit (MMP), that improves the recovery performance of sparse signals. By investigating the multiple paths and then choosing the most promising path in the final moment, the MMP algorithm improves the chance of finding the true support and therefore enhances the recovery performance. From the restricted isometry property (RIP) analysis, we show that the MMP algorithm can perfectly reconstruct any K-sparse (K >1) signals, √provided that the sensing matrix satisfies RIP with δK+L < √ L/√ K +3√ L. We demonstrate by empirical simulations that the MMP algorithm is very competitive in both noisy and noiseless scenarios.
AB - In this paper, we propose a sparse recovery algorithm, termed multiple path matching pursuit (MMP), that improves the recovery performance of sparse signals. By investigating the multiple paths and then choosing the most promising path in the final moment, the MMP algorithm improves the chance of finding the true support and therefore enhances the recovery performance. From the restricted isometry property (RIP) analysis, we show that the MMP algorithm can perfectly reconstruct any K-sparse (K >1) signals, √provided that the sensing matrix satisfies RIP with δK+L < √ L/√ K +3√ L. We demonstrate by empirical simulations that the MMP algorithm is very competitive in both noisy and noiseless scenarios.
UR - http://www.scopus.com/inward/record.url?scp=84890414239&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84890414239&partnerID=8YFLogxK
U2 - 10.1109/ISIT.2013.6620347
DO - 10.1109/ISIT.2013.6620347
M3 - Conference contribution
AN - SCOPUS:84890414239
SN - 9781479904464
T3 - IEEE International Symposium on Information Theory - Proceedings
SP - 854
EP - 858
BT - 2013 IEEE International Symposium on Information Theory, ISIT 2013
T2 - 2013 IEEE International Symposium on Information Theory, ISIT 2013
Y2 - 7 July 2013 through 12 July 2013
ER -