DocumentCode
1298136
Title
Analysis of Orthogonal Matching Pursuit Using the Restricted Isometry Property
Author
Davenport, Mark A. ; Wakin, Michael B.
Author_Institution
Dept. of Stat., Stanford Univ., Stanford, CA, USA
Volume
56
Issue
9
fYear
2010
Firstpage
4395
Lastpage
4401
Abstract
Orthogonal matching pursuit (OMP) is the canonical greedy algorithm for sparse approximation. In this paper we demonstrate that the restricted isometry property (RIP) can be used for a very straightforward analysis of OMP. Our main conclusion is that the RIP of order K+1 (with isometry constant δ <; [ 1/( 3√K)]) is sufficient for OMP to exactly recover any K-sparse signal. The analysis relies on simple and intuitive observations about OMP and matrices which satisfy the RIP. For restricted classes of K-sparse signals (those that are highly compressible), a relaxed bound on the isometry constant is also established. A deeper understanding of OMP may benefit the analysis of greedy algorithms in general. To demonstrate this, we also briefly revisit the analysis of the regularized OMP (ROMP) algorithm.
Keywords
approximation theory; greedy algorithms; iterative methods; K-sparse signal; canonical greedy algorithm; isometry constant; orthogonal matching pursuit; regularized OMP algorithm; relaxed bound; restricted isometry property; sparse approximation; Algorithm design and analysis; Approximation algorithms; Approximation methods; Dictionaries; Greedy algorithms; Matching pursuit algorithms; Pursuit algorithms; Signal processing algorithms; Software algorithms; Software packages; Sparse matrices; Compressive sensing; greedy algorithms; orthogonal matching pursuit (OMP); redundant dictionaries; restricted isometry property (RIP); sparse approximation;
fLanguage
English
Journal_Title
Information Theory, IEEE Transactions on
Publisher
ieee
ISSN
0018-9448
Type
jour
DOI
10.1109/TIT.2010.2054653
Filename
5550495
Link To Document