Analysis of generalised orthogonal matching pursuit using restricted isometry constant

2014 ◽  
Vol 50 (14) ◽  
pp. 1020-1022 ◽  
Author(s):  
Yi Shen ◽  
Bo Li ◽  
Wenlei Pan ◽  
Jia Li
2018 ◽  
Vol 61 (1) ◽  
pp. 40-54 ◽  
Author(s):  
Wengu Chen ◽  
Huanmin Ge

AbstractThe generalized orthogonal matching pursuit (gOMP) algorithm has received much attention in recent years as a natural extension of the orthogonal matching pursuit (OMP). It is used to recover sparse signals in compressive sensing. In this paper, a new bound is obtained for the exact reconstruction of every K-sparse signal via the gOMP algorithm in the noiseless case. That is, if the restricted isometry constant (RIC) δNK+1 of the sensing matrix A satisfiesthen the gOMP can perfectly recover every K-sparse signal x from y = Ax. Furthermore, the bound is proved to be sharp. In the noisy case, the above bound on RIC combining with an extra condition on the minimum magnitude of the nonzero components of K-sparse signals can guarantee that the gOMP selects all of the support indices of the K-sparse signals.


2013 ◽  
Vol 49 (23) ◽  
pp. 1487-1489 ◽  
Author(s):  
Jinming Wen ◽  
Xiaomei Zhu ◽  
Dongfang Li

2020 ◽  
Vol 58 (7) ◽  
pp. 4529-4546
Author(s):  
Ekaterina Shipilova ◽  
Michel Barret ◽  
Matthieu Bloch ◽  
Jean-Luc Boelle ◽  
Jean-Luc Collette

2011 ◽  
Vol 57 (8) ◽  
pp. 5326-5341 ◽  
Author(s):  
Zakria Hussain ◽  
John Shawe-Taylor ◽  
David R. Hardoon ◽  
Charanpal Dhanjal

2013 ◽  
Vol 61 (2) ◽  
pp. 398-410 ◽  
Author(s):  
Jie Ding ◽  
Laming Chen ◽  
Yuantao Gu

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