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CORR
2011
Springer

How well can we estimate a sparse vector?

9 years 6 months ago
How well can we estimate a sparse vector?
The estimation of a sparse vector in the linear model is a fundamental problem in signal processing, statistics, and compressive sensing. This paper establishes a lower bound on the mean-squared error, which holds regardless of the sensing/design matrix being used and regardless of the estimation procedure. This lower bound very nearly matches the known upper bound one gets by taking a random projection of the sparse vector followed by an 1 estimation procedure such as the Dantzig selector. In this sense, compressive sensing techniques cannot essentially be improved.
Emmanuel J. Candès, Mark A. Davenport
Added 13 May 2011
Updated 13 May 2011
Type Journal
Year 2011
Where CORR
Authors Emmanuel J. Candès, Mark A. Davenport
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