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A preconditioner for a primal-dual Newton conjugate gradients method for compressed sensing problems
Date
2016
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 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.
Supervisor
Description
peer-reviewed
Publisher
Society for Industrial and Applied Mathematics (SIAM)
Citation
SIAM Journal on Scientific Computing;37 (6), pp. A2783-A2812
Files
Funding code
Funding Information
Engineering and Physical Sciences Research Council
Sustainable Development Goals
External Link
Type
Article
Rights
https://creativecommons.org/licenses/by-nc-sa/1.0/