RT-FOCUSS Algorithm for Sparse Recovery in Fully-perturbed Linear Model

DOI

10.2991/icmra-15.2015.112How to use a DOI?

Keywords

underdetermined system; fully-perturbed linear model; sparse recovery; RT-FOUCSS

Abstract

In this paper, an improved and regularized algorithm is proposed to solve the sparse recovery problem in “fully-perturbed” model, which means perturbations present both in measurements and dictionary matrix. The paper shows how the regularized algorithm is derived based on TLS (total least-squares) and FOCUSS (FOCal Underdetermined System Solver) methods. In the end, simulations illustrate the advantages of the new algorithm.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

TY  - CONF
AU  - Xuebing Han
AU  - Zhaojun Jiang
PY  - 2015/04
DA  - 2015/04
TI  - RT-FOCUSS Algorithm for Sparse Recovery in Fully-perturbed Linear Model
BT  - Proceedings of the 3rd International Conference on Mechatronics, Robotics and Automation
PB  - Atlantis Press
SP  - 573
EP  - 576
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmra-15.2015.112
DO  - 10.2991/icmra-15.2015.112
ID  - Han2015/04
ER  -