Support detection in super-resolution
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Abstract (arXiv)
We study the problem of super-resolving a superposition of point sources from noisy low-pass data with a cut-off frequency f. Solving a tractable convex program is shown to locate the elements of the support with high precision as long as they are separated by 2/f and the noise level is small with respect to the amplitude of the signal.
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). First posted on arXiv 16 Feb 2013.
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2 papers.