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Spectral Compressive Sensing with Polar Interpolation
[article]
2013
arXiv
pre-print
Existing approaches to compressive sensing of frequency-sparse signals focuses on signal recovery rather than spectral estimation. Furthermore, the recovery performance is limited by the coherence of the required sparsity dictionaries and by the discretization of the frequency parameter space. In this paper, we introduce a greedy recovery algorithm that leverages a band-exclusion function and a polar interpolation function to address these two issues in spectral compressive sensing. Our
arXiv:1303.2799v3
fatcat:ap6g2t552jgsdlif3vj56fcmda