首页> 外文期刊>Journal of Southeast University >Rice condition numbers of QR and Cholesky factorizations
【24h】

Rice condition numbers of QR and Cholesky factorizations

机译:QR和Cholesky分解的水稻条件数

获取原文
获取原文并翻译 | 示例
       

摘要

A condition number is an amplification coefficient due to errors in computing. Thus the theory of condition numbers plays an important role in error analysis. In this paper, following the approach of Rice, condition numbers are defined for factors of some matrix factorizations such as the Cholesky factorization of a symmetric positive definite matrix and QR factorization of a general matrix. The condition numbers are derived by a technique of analytic expansion of the factor dependent on one parameter and matrix-vector equation. Condition numbers of the Cholesky and QR factors are different from the ones previously introduced by other authors, but similar to Chang's results. In Cholesky factorization, corresponding with the condition number of the factor matrix L, K_L is a low bound of Stewart's condition number K.
机译:条件数是归因于计算误差的放大系数。因此,条件数理论在误差分析中起着重要作用。在本文中,按照莱斯的方法,为一些矩阵分解因子定义了条件数,例如对称正定矩阵的Cholesky分解和一般矩阵的QR分解。通过依赖于一个参数和矩阵矢量方程的因子的解析扩展技术来导出条件数。 Cholesky和QR因子的条件数与其他作者先前介绍的条件数不同,但与Chang的结果相似。在Cholesky分解中,与因子矩阵L的条件数相对应,K_L是Stewart条件数K的下界。

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