Moore-Penrose inverse;
Perturbation;
Singular value decomposition;
BOUNDS;
D O I:
10.1016/j.amc.2019.124920
中图分类号:
O29 [应用数学];
学科分类号:
070104 ;
摘要:
The Moore-Penrose inverse of a matrix has been extensively investigated and widely applied in many fields over the past decades. One reason for the interest is that the Moore-Penrose inverse can succinctly express some important geometric constructions in finite-dimensional spaces, such as the orthogonal projection onto a subspace and the linear least squares problem. In this paper, we establish new perturbation bounds for the Moore-Penrose inverse under the Frobenius norm, some of which are sharper than the existing ones. (C) 2020 Elsevier Inc. All rights reserved.