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Preconditioned GAOR methods for solving weighted linear least squares problems

机译:求解加权线性最小二乘问题的预处理GAOR方法

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摘要

In this paper, we present the preconditioned generalized accelerated overrelaxation (GAOR) method for solving linear systems based on a class of weighted linear least square problems. Two kinds of preconditioning are proposed, and each one contains three preconditioners. We compare the spectral radii of the iteration matrices of the preconditioned and the original methods. The comparison results show that the convergence rate of the preconditioned GAOR methods is indeed better than the rate of the original method, whenever the original method is convergent. Finally, a numerical example is presented in order to confirm these theoretical results. (C) 2008 Elsevier B.V. All rights reserved.
机译:在本文中,我们提出了基于一类加权线性最小二乘问题的线性系统的预处理广义加速过松弛(GAOR)方法。提出了两种预处理,每种预处理包含三个预处理器。我们比较了预处理和原始方法的迭代矩阵的谱半径。比较结果表明,每当原始方法收敛时,预处理GAOR方法的收敛速度确实好于原始方法的收敛速度。最后,给出一个数值例子,以证实这些理论结果。 (C)2008 Elsevier B.V.保留所有权利。

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