Greedy Signal Recovery Review
Creators
Abstract
The two major approaches to sparse recovery are L_1-minimization and greedy methods. Recently, Needell and Vershynin developed regularized orthogonal matching pursuit (ROMP) that has bridged the gap between these two approaches. ROMP is the first stable greedy algorithm providing uniform guarantees. Even more recently, Needell and Tropp developed the stable greedy algorithm compressive sampling matching pursuit (CoSaMP). CoSaMP provides uniform guarantees and improves upon the stability bounds and RIC requirements of ROMP. CoSaMP offers rigorous bounds on computational cost and storage. In many cases, the running time is just O(N log N), where N is the ambient dimension of the signal. This review summarizes these major advances.
Additional Information
© 2008 IEEE.Attached Files
Published - 05074572.pdf
Accepted Version - 0812.2202.pdf
Files
05074572.pdf
Files
(342.1 kB)
| Name | Size | Download all |
|---|---|---|
|
md5:0b3294d1f17848d4d93d3e22a65a5fe6
|
214.7 kB | Preview Download |
|
md5:a50326e93a659cd834fc2b9394a718bb
|
127.3 kB | Preview Download |
Additional details
Identifiers
- Eprint ID
- 89330
- Resolver ID
- CaltechAUTHORS:20180831-112109709
Related works
- Describes
- http://arxiv.org/abs/0812.2202 (URL)
Dates
- Created
-
2018-09-04Created from EPrint's datestamp field
- Updated
-
2021-11-16Created from EPrint's last_modified field