首页> 外文期刊>Journal of Mathematics and Statistics >MINIMIZATION OF ?2-NORM OF THE KSOR OPERATOR | Science Publications
【24h】

MINIMIZATION OF ?2-NORM OF THE KSOR OPERATOR | Science Publications

机译:KSOR算子的α2-范数的最小化科学出版物

获取原文
       

摘要

> We consider the problem of minimizing the ?2-norm of the KSOR operator when solving a linear systems of the form AX = b where, A = I +B (TJ = -B, is the Jacobi iteration matrix), B is skew symmetric matrix. Based on the eigenvalue functional relations given for the KSOR method, we find optimal values of the relaxation parameter which minimize the ?2-norm of the KSOR operators. Use the Singular Value Decomposition (SVD) techniques to find an easy computable matrix unitary equivalent to the iteration matrix TKSOR. The optimum value of the relaxation parameter in the KSOR method is accurately approximated through the minimization of the ?2-norm of an associated matrix ?(?*) which has the same spectrum as the iteration matrix. Numerical example illustrating and confirming the theoretical relations are considered. Using SVD is an easy and effective approach in proving the eigenvalue functional relations and in determining the appropriate value of the relaxation parameter. All calculations are performed with the help of the computer algebra system ?Mathematica 8.0?.
机译: >当求解形式为AX = b的线性系统时,我们考虑最小化KSOR运算符的? 2 -范数的问题,其中A = I + B(T < sub> J = -B,是Jacobi迭代矩阵),B是倾斜对称矩阵。根据针对KSOR方法给出的特征值函数关系,我们找到了使KSOR算子的 sub> 2 -范数最小的松弛参数的最佳值。使用奇异值分解(SVD)技术找到与迭代矩阵T KSOR 等效的简单可计算矩阵unit。 KSOR方法中松弛参数的最佳值是通过最小化具有相同矩阵的关联矩阵?(? * )的? 2 范数来精确估算的频谱作为迭代矩阵。考虑说明和证实理论关系的数值示例。使用SVD是证明特征值函数关系和确定松弛参数的适当值的简便有效的方法。所有计算均在计算机代数系统“ Mathematica 8.0”的帮助下进行。

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