Perturbation Analysis and Randomized Algorithms for Large-Scale Total Least Squares Problems
Numerical Analysis
2014-11-12 v2
Abstract
In this paper, we present perturbation analysis and randomized algorithms for the total least squares (TLS) problems. We derive the perturbation bound and check its sharpness by numerical experiments. Motivated by the recently popular probabilistic algorithms for low-rank approximations, we develop randomized algorithms for the TLS and the truncated total least squares (TTLS) solutions of large-scale discrete ill-posed problems, which can greatly reduce the computational time and still keep good accuracy.
Cite
@article{arxiv.1401.6832,
title = {Perturbation Analysis and Randomized Algorithms for Large-Scale Total Least Squares Problems},
author = {Pengpeng Xie and Yimin Wei and Hua Xiang},
journal= {arXiv preprint arXiv:1401.6832},
year = {2014}
}
Comments
27 pages, 10 figures, 8 tables