时间：2014年11月28日（周五）9：30-10：30

地点：下沙校区教学D楼106（理学院党员之家）

摘要：

Classical condition numbers are normwise: they measure the size of both input perturbations and output errors using some norms. To take into account the relative of each data component, and, in particular, a possible data sparseness, componentwise condition numbers have been increasingly considered. These are mostly of two kinds: mixed and componentwise. In this talk, we give explicit expressions, computable from the data, for the mixed and componentwise condition numbers for the computation of the Moore-Penrose inverse as well as for the computation of solutions and residues of linear least squares and total least squares, matrix equations and Tikhonov regularization problems. In both cases the data matrices have full column (row) rank.

专家简介：

    魏益民教授，1997年获复旦大学数学研究所理学博士学位，计算数学博士生导师。现为美国数学评论评论员。国际线性代数学会(ILAS)，美国数学会，中国计算数学学会—线性代数专业委员会委员会员。同时担任Linear Algebra and its Applications， FILOMAT，高校计算数学学报等多个杂志的编委。