RT-FOCUSS Algorithm for Sparse Recovery in Fully-perturbed Linear Model
Xuebing Han, Zhaojun Jiang
Available Online April 2015.
- https://doi.org/10.2991/icmra-15.2015.112How to use a DOI?
- underdetermined system; fully-perturbed linear model; sparse recovery; RT-FOUCSS
- 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.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
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 - 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 - https://doi.org/10.2991/icmra-15.2015.112 ID - Han2015/04 ER -