Compressed sensing for inverse problems II: applications to
deconvolution, source recovery, and MRI
Compressed sensing for inverse problems II: applications to
deconvolution, source recovery, and MRI
This paper extends the sample complexity theory for ill-posed inverse problems developed in a recent work by the authors [`Compressed sensing for inverse problems and the sample complexity of the sparse Radon transform', J. Eur. Math. Soc., to appear], which was originally focused on the sparse Radon transform. We demonstrate …