- Journal Home
- Volume 39 - 2021
- Volume 38 - 2020
- Volume 37 - 2019
- Volume 36 - 2018
- Volume 35 - 2017
- Volume 34 - 2016
- Volume 33 - 2015
- Volume 32 - 2014
- Volume 31 - 2013
- Volume 30 - 2012
- Volume 29 - 2011
- Volume 28 - 2010
- Volume 27 - 2009
- Volume 26 - 2008
- Volume 25 - 2007
- Volume 24 - 2006
- Volume 23 - 2005
- Volume 22 - 2004
- Volume 21 - 2003
- Volume 20 - 2002
- Volume 19 - 2001
- Volume 18 - 2000
- Volume 17 - 1999
- Volume 16 - 1998
- Volume 15 - 1997
- Volume 14 - 1996
- Volume 13 - 1995
- Volume 12 - 1994
- Volume 11 - 1993
- Volume 10 - 1992
- Volume 9 - 1991
- Volume 8 - 1990
- Volume 7 - 1989
- Volume 6 - 1988
- Volume 5 - 1987
- Volume 4 - 1986
- Volume 3 - 1985
- Volume 2 - 1984
- Volume 1 - 1983
The Exact Recovery of Sparse Signals Via Orthogonal Matching Pursuit
- BibTex
- RIS
- TXT
@Article{JCM-34-70,
author = {Liao , Anping and Xie , Jiaxin and Yang , Xiaobo and Wang , Peng },
title = {The Exact Recovery of Sparse Signals Via Orthogonal Matching Pursuit},
journal = {Journal of Computational Mathematics},
year = {2016},
volume = {34},
number = {1},
pages = {70--86},
abstract = { This paper aims to investigate sufficient conditions for the recovery of sparse signals via the orthogonal matching pursuit (OMP) algorithm. In the noiseless case, we present a novel sufficient condition for the exact recovery of all k-sparse signals by the OMP algorithm, and demonstrate that this condition is sharp. In the noisy case, a sufficient condition for recovering the support of k-sparse signal is also presented. Generally, the computation for the restricted isometry constant (RIC) in these sufficient conditions is typically difficult, therefore we provide a new condition which is not only computable but also sufficient for the exact recovery of all k-sparse signals.},
issn = {1991-7139},
doi = {https://doi.org/10.4208/jcm.1510-m2015-0284},
url = {http://global-sci.org/intro/article_detail/jcm/9783.html}
}
TY - JOUR
T1 - The Exact Recovery of Sparse Signals Via Orthogonal Matching Pursuit
AU - Liao , Anping
AU - Xie , Jiaxin
AU - Yang , Xiaobo
AU - Wang , Peng
JO - Journal of Computational Mathematics
VL - 1
SP - 70
EP - 86
PY - 2016
DA - 2016/02
SN - 34
DO - http://doi.org/10.4208/jcm.1510-m2015-0284
UR - https://global-sci.org/intro/article_detail/jcm/9783.html
KW - Compressed sensing
KW - Sparse signal recovery
KW - Restricted orthogonality constant (ROC)
KW - Restricted isometry constant (RIC)
KW - Orthogonal matching pursuit (OMP)
AB - This paper aims to investigate sufficient conditions for the recovery of sparse signals via the orthogonal matching pursuit (OMP) algorithm. In the noiseless case, we present a novel sufficient condition for the exact recovery of all k-sparse signals by the OMP algorithm, and demonstrate that this condition is sharp. In the noisy case, a sufficient condition for recovering the support of k-sparse signal is also presented. Generally, the computation for the restricted isometry constant (RIC) in these sufficient conditions is typically difficult, therefore we provide a new condition which is not only computable but also sufficient for the exact recovery of all k-sparse signals.
Anping Liao , Jiaxin Xie , Xiaobo Yang & Peng Wang . (2019). The Exact Recovery of Sparse Signals Via Orthogonal Matching Pursuit.
Journal of Computational Mathematics. 34 (1).
70-86.
doi:10.4208/jcm.1510-m2015-0284
Copy to clipboard