论文标题
重新启动的随机周围方法求解大型线性方程
Restarted randomized surrounding methods for solving large linear equations
论文作者
论文摘要
提出了一类重新启动的随机周围方法，以通过重新启动求解线性方程的技术来加速周围的算法。理论分析证明，所提出的方法在随机行选择规则和期望收敛速率下收敛。数值实验进一步表明，所提出的算法是有效的，并且胜过现有的过度确定和不确定的线性方程以及图像处理的应用。
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.
