The achievable performance of convex demixing

Michael B. McCoy; Joel A. Tropp

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arXiv · 1309.7478

The achievable performance of convex demixing

Michael B. McCoy·Joel A. Tropp

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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.

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Michael B. McCoy, Joel A. Tropp. 2013-09-28. The achievable performance of convex demixing. https://arxiv.org/abs/1309.7478

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