Finding the closest normal structured matrix

Fuente: arXiv
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Main Author: Begovic, Erna
Format: Preprint
Published: 2020
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_version_ 1866913270510649344
author Begovic, Erna
author_facet Begovic, Erna
contents Given a structured matrix $A$ we study the problem of finding the closest normal matrix with the same structure. The structures of our interest are: Hamiltonian, skew-Hamiltonian, per-Hermitian, and perskew-Hermitian. We develop a structure-preserving Jacobi-type algorithm for finding the closest normal structured matrix and show that such algorithm converges to a stationary point of the objective function.
format Preprint
id arxiv_https___arxiv_org_abs_2003_06391
institution arXiv
publishDate 2020
record_format arxiv
spellingShingle Finding the closest normal structured matrix
Begovic, Erna
Numerical Analysis
15B57, 15A23, 65F99
Given a structured matrix $A$ we study the problem of finding the closest normal matrix with the same structure. The structures of our interest are: Hamiltonian, skew-Hamiltonian, per-Hermitian, and perskew-Hermitian. We develop a structure-preserving Jacobi-type algorithm for finding the closest normal structured matrix and show that such algorithm converges to a stationary point of the objective function.
title Finding the closest normal structured matrix
topic Numerical Analysis
15B57, 15A23, 65F99
url https://arxiv.org/abs/2003.06391