...
首页> 外文期刊>Journal of Computational and Applied Mathematics >A variable preconditioned GCR(m) method using the GSOR method for singular and rectangular linear systems
【24h】

A variable preconditioned GCR(m) method using the GSOR method for singular and rectangular linear systems

机译:使用GSOR方法的奇异和矩形线性系统的可变预处理GCR(m)方法

获取原文
获取原文并翻译 | 示例
           

摘要

The Generalized Conjugate Residual (GCR) method with a variable preconditioning is an efficient method for solving a large sparse linear system Ax = b. It has been clarified by some numerical experiments that the Successive Over Relaxation (SOR) method is more effective than Krylov subspace methods such as GCR and ILU(0) preconditioned GCR for performing the variable preconditioning. However, SOR cannot be applied for performing the variable preconditioning when solving such linear systems that the coefficient matrix has diagonal entries of zero or is not square. Therefore, we propose a type of the generalized SOR (GSOR) method. By numerical experiments on the singular linear systems, we demonstrate that the variable preconditioned GCR using GSOR is effective.
机译:具有可变预条件的广义共轭残差(GCR)方法是解决大型稀疏线性系统Ax = b的有效方法。通过一些数值实验已经阐明,相继松弛法(SOR)比Krylov子空间方法(例如GCR和ILU(0)预处理GCR)更有效地执行可变预处理。但是,当求解系数矩阵的对角线项为零或不为平方的线性系统时,SOR不能用于执行变量预处理。因此,我们提出了一种广义的SOR(GSOR)方法。通过对奇异线性系统的数值实验,我们证明了使用GSOR进行变量预处理GCR是有效的。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号