Mathematics for various disciplines On mixed and componentwise condition numbers for MoorePenrose inverse and linear least squares problems
 Date

20080806 13:00 
20080806 14:00
 Place
 Graduate School of Mathematical Sciences the University of Tokyo, Room #052

Speaker/Organizer
 Yimin Wei (Fudan University, P.R. of China)

 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 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 MoorePenrose inverse as well as for the computation of solutions and residues of linear least squares problems. In both cases the data matrices have full column (row) rank.
http://coe.math.sci.hokudai.ac.jp/sympo/various/index_en.html