Sharp Recovery Bounds for Convex Demixing, with Applications

Demixing refers to the challenge of identifying two structured signals given only the sum of the two signals and prior information about their structures. Examples include the problem of separating a signal that is sparse with respect to one basis from a signal that is sparse with respect to a secon...

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Veröffentlicht in:	Foundations of computational mathematics Jg. 14; H. 3; S. 503 - 567
Hauptverfasser:	McCoy, Michael B., Tropp, Joel A.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Boston Springer US 01.06.2014 Springer Nature B.V
Schlagworte:	Applications of Mathematics Complexity Computer Science Decoding Demixing Economics Empirical analysis Foundations Linear and Multilinear Algebras Math Applications in Computer Science Mathematical models Mathematics Mathematics and Statistics Matrix Matrix Theory Numerical Analysis Optimization Signal processing Statistics Integral geometry 60D05 Demixing Sparsity Convex optimization 52B55 52A22 (primary) 94B75 (secondary)
ISSN:	1615-3375, 1615-3383
Online-Zugang:	Volltext
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