1 research outputs found
Non-Convex Compressed Sensing Using Partial Support Information
In this paper we address the recovery conditions of weighted
minimization for signal reconstruction from compressed sensing measurements
when partial support information is available. We show that weighted
minimization with is stable and robust under weaker sufficient
conditions compared to weighted minimization. Moreover, the sufficient
recovery conditions of weighted are weaker than those of regular
minimization if at least of the support estimate is accurate. We
also review some algorithms which exist to solve the non-convex
problem and illustrate our results with numerical experiments.Comment: 22 pages, 10 figure