Restarted randomized surrounding methods for solving large linear equations
Numerical Analysis
2022-07-12 v2 Numerical Analysis
Abstract
A class of restarted randomized surrounding methods are presented to accelerate the surrounding algorithms by restarted techniques for solving the linear equations. Theoretical analysis prove that the proposed method converges under the randomized row selection rule and the expectation convergence rate is also addressed. Numerical experiments further demonstrate that the proposed algorithms are efficient and outperform the existing method for over-determined and under-determined linear equation, as well as in the application of image processing.
Cite
@article{arxiv.2205.01388,
title = {Restarted randomized surrounding methods for solving large linear equations},
author = {Junfeng Yin and Nan Li and Ning Zheng},
journal= {arXiv preprint arXiv:2205.01388},
year = {2022}
}