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Preconditioned iterative methods for solving weighted linear least squares problems 被引量:2

Preconditioned iterative methods for solving weighted linear least squares problems
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摘要 A class of preconditioned iterative methods, i.e., preconditioned generalized accelerated overrelaxation (GAOR) methods, is proposed to solve linear systems based on a class of weighted linear least squares problems. The convergence and comparison results are obtained. The comparison results show that the convergence rate of the preconditioned iterative methods is better than that of the original methods. Furthermore, the effectiveness of the proposed methods is shown in the numerical experiment. A class of preconditioned iterative methods, i.e., preconditioned generalized accelerated overrelaxation (GAOR) methods, is proposed to solve linear systems based on a class of weighted linear least squares problems. The convergence and comparison results are obtained. The comparison results show that the convergence rate of the preconditioned iterative methods is better than that of the original methods. Furthermore, the effectiveness of the proposed methods is shown in the numerical experiment.
出处 《Applied Mathematics and Mechanics(English Edition)》 SCIE EI 2012年第3期375-384,共10页 应用数学和力学(英文版)
基金 supported by the National Natural Science Foundation of China (No. 11071033) the Fundamental Research Funds for the Central Universities (No. 090405013)
关键词 PRECONDITIONER generalized accelerated overrelaxation (GAOR) method weighted linear least squares problem CONVERGENCE preconditioner, generalized accelerated overrelaxation (GAOR) method weighted linear least squares problem, convergence
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