Shrinkage rules for variational minimization problems and applications to analytical ultracentrifugation
Shrinkage rules for variational minimization problems and applications to analytical ultracentrifugation
Abstract Finding a sparse representation of a noisy signal can be modeled as a variational minimization with -sparsity constraints for q less than one. Especially for real-time, online, or iterative applications, in which problems of this type have to be solved multiple times, one needs fast algorithms to compute these …