Published July 2011
| Accepted Version
Book Section - Chapter
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Explicit Matrices for Sparse Approximation
Abstract
We show that girth can be used to certify that sparse compressed sensing matrices have good sparse approximation guarantees. This allows us to present the first deterministic measurement matrix constructions that have an optimal number of measurements for ℓ_1/ℓ_1 approximation. Our techniques are coding theoretic and rely on a recent connection of compressed sensing to LP relaxations for channel decoding.
Additional Information
© 2011 IEEE. Date of Current Version: 03 October 2011.Attached Files
Accepted Version - Explicit_20matrices_20for_20sparse_20approximation.pdf
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Explicit_20matrices_20for_20sparse_20approximation.pdf
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Additional details
- Eprint ID
- 29990
- DOI
- 10.1109/ISIT.2011.6034170
- Resolver ID
- CaltechAUTHORS:20120405-093333989
- Created
-
2012-04-05Created from EPrint's datestamp field
- Updated
-
2021-11-09Created from EPrint's last_modified field
- Other Numbering System Name
- INSPEC Accession Number
- Other Numbering System Identifier
- 12289109