150 citations · 480 across the 12 of their papers we have counts for
3 papers · 1 filter
Compressed Sensing with 1D Total Variation: Breaking Sample Complexity Barriers via Non-Uniform Recovery (iTWIST'20)
Martin Genzel, Maximilian März, Robert Seidel
This paper investigates total variation minimization in one spatial dimension for the recovery of gradient-sparse signals from undersampled Gaussian measurements. Recently establis…
Compressed Sensing with 1D Total Variation: Breaking Sample Complexity Barriers via Non-Uniform Recovery
Martin Genzel, Maximilian März, Robert Seidel
This paper investigates total variation minimization in one spatial dimension for the recovery of gradient-sparse signals from undersampled Gaussian measurements. Recently establis…
-Analysis Minimization and Generalized (Co-)Sparsity: When Does Recovery Succeed?
Martin Genzel, Gitta Kutyniok, Maximilian März
This paper investigates the problem of signal estimation from undersampled noisy sub-Gaussian measurements under the assumption of a cosparse model. Based on generalized notions of…