Journal article
Performance comparisons of greedy algorithms in compressed sensing
- Abstract:
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Compressed sensing has motivated the development of numerous sparse approximation algorithms designed to return a solution to an underdetermined system of linear equations where the solution has the fewest number of nonzeros possible, referred to as the sparsest solution. In the compressed sensing setting, greedy sparse approximation algorithms have been observed to be both able to recover the sparsest solution for similar problem sizes as other algorithms and to be computationally efficient;...
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- Publication status:
- Published
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(Pre-print, pdf, 4.6MB)
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- Publisher copy:
- 10.1002/nla.1948
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Funding
Bibliographic Details
- Journal:
- Numerical Linear Algebra with Applications
- Volume:
- 22
- Issue:
- 2
- Pages:
- 254-282
- Publication date:
- 2015-03-01
- DOI:
- EISSN:
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1099-1506
- ISSN:
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1070-5325
- Source identifiers:
-
478275
Item Description
- Language:
- English
- Keywords:
- Pubs id:
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pubs:478275
- UUID:
-
uuid:4f8b7b8f-cf0b-450f-90f6-59883b0c5255
- Local pid:
- pubs:478275
- Deposit date:
- 2015-09-21
Terms of use
- Copyright holder:
- John Wiley and Sons, Inc
- Copyright date:
- 2015
- Notes:
- This is the pre-peer reviewed version of the article which has been published in final form at DOI: 10.1002/nla.1948. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving
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