期刊文献+

向量范数与矩阵范数的相容性研究

Study on Compatibility between Vector Norms and Matrix Norms
下载PDF
导出
摘要 针对范数理论在研究算法的收敛性、稳定性以及误差分析中的重要应用,从向量范数出发,引入矩阵范数,进一步讨论向量范数与矩阵范数的相容性问题,给出了求与向量范数相容的矩阵范数的方法,并得出算子范数即为与向量范数相容的矩阵范数。 in view of the important application of norm theory in the study of convergence,stability and error analysis of the algorithm,the matrix norm is introduced from the vector norm to further discuss the compatibility the vector norm and the matrix norm is further discussed.The method of finding matrix norm compatible with vec⁃tor norm is given,and the operator norm is the matrix norm compatible with vector norm.
作者 田东霞 TIAN Dongxia(Fenyang Normal School of Lvliang University,Fenyang 032200,China)
出处 《安阳工学院学报》 2020年第4期89-91,共3页 Journal of Anyang Institute of Technology
关键词 向量范数 矩阵范数 算子范数 相容性 vector norm matrix norm operator norm compatibility
  • 相关文献

参考文献8

二级参考文献32

  • 1马秀珍,韩静华.关于几种广义逆矩阵及其应用的探讨[J].沈阳航空工业学院学报,2005,22(2):74-75. 被引量:8
  • 2李玉清.关于矩阵范数的4个等式[J].陕西理工学院学报(自然科学版),2005,21(3):87-89. 被引量:1
  • 3Monteiro R D C. Primal-dual path following interior point algorithms for semi-definite programming[J]. SIAM J Optimization, 1997,7 (3) : 663-678.
  • 4Renato D C Monteiro,Takashi Tsuchiya. Polynomial convergence of a new family of primal-dual algorithms for semi-definite programming[J]. SIAM J Optimization, 1999, 9 (3) : 551-577.
  • 5Zhang Yin. On extending some primal-dual interior point algorithms from linear programming to semidefinite programming [J] . SIAMJ Optimization 1998,8 (2) : 365-386.
  • 6Horn R A, Johnson C R. Topics in matrix analysis [M]. New York: Cambridge University Press, 1991.
  • 7合恩,约翰逊,杨奇译.矩阵分析[M].北京:机械工业出版社,2005.
  • 8HORN R A,JOHNSON C R.Matrix analysis[M].Cambridge:Cambridge University Press,1986:487-529.
  • 9HENRY MINC.Nonnegative matrices[M].New York:Wiley-Interscience Publication,1988:1-47,105-140.
  • 10BERMAN A,PLEMMONS R.Nonnegative matrices in the mathematical sciences[M].New York:Academic Press,1994:26-59,211-268.

共引文献9

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部