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CORR
2010
Springer

High-Dimensional Matched Subspace Detection When Data are Missing

13 years 3 months ago
High-Dimensional Matched Subspace Detection When Data are Missing
We consider the problem of deciding whether a highly incomplete signal lies within a given subspace. This problem, Matched Subspace Detection, is a classical, wellstudied problem when the signal is completely observed. Highdimensional testing problems in which it may be prohibitive or impossible to obtain a complete observation motivate this work. The signal is represented as a vector in Rn , but we only observe m n of its elements. We show that reliable detection is possible, under mild incoherence conditions, as long as m is slightly greater than the dimension of the subspace in question.
Laura Balzano, Benjamin Recht, Robert Nowak
Added 09 Dec 2010
Updated 09 Dec 2010
Type Journal
Year 2010
Where CORR
Authors Laura Balzano, Benjamin Recht, Robert Nowak
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