Published September 28, 2013
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The achievable performance of convex demixing
- Creators
- McCoy, Michael B.
- Tropp, Joel A.
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.
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.Attached Files
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Additional details
- Eprint ID
- 89336
- Resolver ID
- CaltechAUTHORS:20180831-112130540
- 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 Foundation
- Created
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2018-09-04Created from EPrint's datestamp field
- Updated
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2023-06-02Created from EPrint's last_modified field