A Preconditioner for a Primal-Dual Newton Conjugate Gradients Method for Compressed Sensing Problems

Ioannis Dassios, Kimon Fountoulakis, Jacek Gondzio

Research output: Contribution to journalArticlepeer-review

Abstract

In this paper we are concerned with the solution of Compressed Sensing (CS) problems where the signals to be recovered are sparse in coherent and redundant dictionaries. We extend the primal-dual Newton Conjugate Gradients (pdNCG) method in [9] for CS problems. We provide an inexpensive and provably effective preconditioning technique for linear systems using pdNCG. Numerical results are presented on CS problems which demonstrate the performance of pdNCG with the proposed preconditioner compared to state-of-the-art existing solvers.
Original languageEnglish
Pages (from-to)A2783-A2812
Number of pages30
JournalSIAM Journal on Scientific Computing
Volume37
Issue number6
Early online date24 Nov 2015
DOIs
Publication statusE-pub ahead of print - 24 Nov 2015

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