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The achievable performance of convex demixing

McCoy, Michael B. and Tropp, Joel A. (2013) The achievable performance of convex demixing. . (Unpublished) https://resolver.caltech.edu/CaltechAUTHORS:20180831-112130540

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Abstract

Demixing is the problem of identifying multiple structured signals from a superimposed, undersampled, and noisy observation. This work analyzes a general framework, based on convex optimization, for solving demixing problems. When the constituent signals follow a generic incoherence model, this analysis leads to precise recovery guarantees. These results admit an attractive interpretation: each signal possesses an intrinsic degrees-of-freedom parameter, and demixing can succeed if and only if the dimension of the observation exceeds the total degrees of freedom present in the observation.


Item Type:Report or Paper (Discussion Paper)
Related URLs:
URLURL TypeDescription
http://arxiv.org/abs/1309.7478arXivDiscussion Paper
ORCID:
AuthorORCID
Tropp, Joel A.0000-0003-1024-1791
Additional Information:MBM thanks Prof. Leonard Schulman for helpful conversations about this research. This research was supported by ONR awards N00014-08-1-0883 and N00014-11-1002, AFOSR award FA9550-09-1-0643, and a Sloan Research Fellowship.
Funders:
Funding AgencyGrant Number
Office of Naval Research (ONR)N00014-08-1-0883
Office of Naval Research (ONR)N00014-11-1002
Air Force Office of Scientific Research (AFOSR)FA9550-09-1-0643
Alfred P. Sloan FoundationUNSPECIFIED
Record Number:CaltechAUTHORS:20180831-112130540
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20180831-112130540
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:89336
Collection:CaltechAUTHORS
Deposited By: George Porter
Deposited On:04 Sep 2018 14:48
Last Modified:03 Oct 2019 20:15

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