2016
Sparsity-based reconstruction method for signals with finite rate of innovation
ICASSP 2016accepted
In the last decade, it was shown that it is possible to reconstruct signals with finite rate of innovation (FRI signals) from the samples of their filtered versions. However, when noise is present, the present reconstruction algorithms tend to be low accuracy. In this work, a new sparsity-based reco…