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Spectral compressive sensing with polar interpolation
2013
2013 IEEE International Conference on Acoustics, Speech and Signal Processing
Existing approaches to compressive sensing of frequencysparse 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
doi:10.1109/icassp.2013.6638862
dblp:conf/icassp/FyhnDD13
fatcat:xe6h3gm3qbhlnhbhc4ujef74aa