Emergent Mind
Support detection in super-resolution
(1302.3921)
Published Feb 16, 2013
in
cs.IT
,
math.IT
,
math.NA
,
and
math.OC
Abstract
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.
We're not able to analyze this paper right now due to high demand.
Please check back later (sorry!).
Generate a summary of this paper on our Pro plan:
We ran into a problem analyzing this paper.