Search

In this paper we develop flexible Krylov methods for efficiently computing regularized solutions to large-scale linear inverse problems with an `2 fit-to-data term and an `p penalization term, for p ≥ 1. First we approximate the...

Flexible Golub–Kahan Hybrid regularization Image deblurring Iterative reweighted norm Sparsity reconstruction `p regularization /dk/atira/pure/subjectarea/asjc/2600/2605 name=Computational Mathematics /dk/atira/pure/subjectarea/asjc/2600/2604 name=Applied Mathematics

In this paper we develop flexible Krylov methods for efficiently computing regularized solutions to large-scale linear inverse problems with an `2 fit-to-data term and an `p penalization term, for p ≥ 1. First we approximate the...

Flexible Golub–Kahan Hybrid regularization Image deblurring Iterative reweighted norm Sparsity reconstruction `p regularization /dk/atira/pure/subjectarea/asjc/2600/2605 name=Computational Mathematics /dk/atira/pure/subjectarea/asjc/2600/2604 name=Applied Mathematics