- Abstract:
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We present a new recovery analysis for a standard compressed sensing algorithm, Iterative Hard Thresholding (IHT) (Blumensath and Davies, 2008), which considers the fixed points of the algorithm. In the context of arbitrary measurement matrices, we derive a sufficient condition for the convergence of IHT to a fixed point and a necessary condition for the existence of fixed points. These conditions allow us to perform a sparse signal recovery analysis in the deterministic noiseless case by imp...
Expand abstract - Publication status:
- Published
- Peer review status:
- Peer reviewed
- Version:
- Accepted Manuscript
- Files:
-
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(pdf, 895.7KB)
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- Publisher copy:
- 10.1109/TIT.2015.2399919
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- Publisher:
- IEEE Publisher's website
- Journal:
- IEEE Transactions on Information Theory Journal website
- Volume:
- 61
- Issue:
- 4
- Pages:
- 2019-2042
- Publication date:
- 2015-04-05
- DOI:
- EISSN:
-
1557-9654
- ISSN:
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0018-9448
- URN:
-
uuid:19b06a3e-a98e-495b-a4a3-f8a045eb68b3
- Source identifiers:
-
521210
- Local pid:
- pubs:521210
- Keywords:
- Copyright holder:
- IEEE
- Copyright date:
- 2015
- Notes:
- Copyright © 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.
Journal article
A new and improved quantitative recovery analysis for iterative hard thresholding algorithms in compressed sensing
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