Compressive sensing with redundant dictionaries and structured measurements
Compressive sensing with redundant dictionaries and structured measurements
Sparse approximation methods for the recovery of signals from undersampled data when the signal is sparse in an overcomplete dictionary have received much attention recently due to their practical importance. A common assumption is the D-restricted isometry property (D-RIP), which asks that the sampling matrix approximately preserve the norm of …