Welcome to the new version of CaltechAUTHORS. Login is currently restricted to library staff. If you notice any issues, please email coda@library.caltech.edu
Published 2015 | public
Book Section - Chapter Open

Convex Recovery of a Structured Signal from Independent Random Linear Measurements


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


Files (317.1 kB)
Name Size Download all
317.1 kB Preview Download

Additional details

August 20, 2023
August 20, 2023