Published 2015
| Submitted
Book Section - Chapter
Open
Convex Recovery of a Structured Signal from Independent Random Linear Measurements
- Creators
-
Tropp, Joel A.
- Other:
- Pfander, Götz E.
Chicago
An error occurred while generating the citation.
Abstract
This chapter develops a theoretical analysis of the convex programming method for recovering a structured signal from independent random linear measurements. This technique delivers bounds for the sampling complexity that are similar to recent results for standard Gaussian measurements, but the argument applies to a much wider class of measurement ensembles. To demonstrate the power of this approach, the chapter presents a short analysis of phase retrieval by trace-norm minimization. The key technical tool is a framework, due to Mendelson and coauthors, for bounding a nonnegative empirical process.
Additional Information
© 2015 Springer International Publishing Switzerland. JAT gratefully acknowledges support from ONR award N00014-11-1002, AFOSR award FA9550-09-1-0643, and a Sloan Research Fellowship. Thanks are also due to the Moore Foundation.Attached Files
Submitted - 1405.1102v3.pdf
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Additional details
- Eprint ID
- 69748
- DOI
- 10.1007/978-3-319-19749-4_2
- Resolver ID
- CaltechAUTHORS:20160818-084011981
- Office of Naval Research (ONR)
- N00014-11-1002
- Air Force Office of Scientific Research (AFOSR)
- FA9550-09-1-0643
- Alfred P. Sloan Foundation
- Gordon and Betty Moore Foundation
- Created
-
2016-08-18Created from EPrint's datestamp field
- Updated
-
2021-11-11Created from EPrint's last_modified field
- Series Name
- Applied and Numerical Harmonic Analysi