Structured mapping problems for linearly structured matrices
Numerical Analysis
2013-09-11 v1
Abstract
Given an appropriate class of structured matrices S; we characterize matrices X and B for which there exists a matrix A \in S such that AX = B and determine all matrices in S mapping X to B. We also determine all matrices in S mapping X to B and having the smallest norm. We use these results to investigate structured backward errors of approximate eigenpairs and approximate invariant subspaces, and structured pseudospectra of structured matrices.
Cite
@article{arxiv.1309.2522,
title = {Structured mapping problems for linearly structured matrices},
author = {Bibhas Adhikari and Rafikul Alam},
journal= {arXiv preprint arXiv:1309.2522},
year = {2013}
}
Comments
15 pages