
doi: 10.1002/nla.838
SUMMARYPerturbation bounds for Moore–Penrose inverses of rectangular matrices play a significant role in the perturbation analysis for linear least squares problems. In this note, we derive a sharp upper bound for Moore–Penrose inverses, which is better than a well known existing one. Copyright © 2011 John Wiley & Sons, Ltd.
numerical examples, Numerical solutions to overdetermined systems, pseudoinverses, Numerical computation of matrix norms, conditioning, scaling, acute perturbation, linear least squares problems, perturbation bounds, Theory of matrix inversion and generalized inverses, Moore-Penrose inverse, stable perturbation
numerical examples, Numerical solutions to overdetermined systems, pseudoinverses, Numerical computation of matrix norms, conditioning, scaling, acute perturbation, linear least squares problems, perturbation bounds, Theory of matrix inversion and generalized inverses, Moore-Penrose inverse, stable perturbation
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 18 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
