Least-squares solutions of the equation AX=B over anti-Hermitian generalized Hamiltonian matrices
Numer. Math. J. Chinese Univ. (English Ser.)(English Ser.) 15 (2006), pp. 60-66
Published online: 2006-02
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@Article{NM-15-60,
author = {Z. Zhang and C. Liu},
title = {Least-squares solutions of the equation AX=B over anti-Hermitian generalized Hamiltonian matrices},
journal = {Numerical Mathematics, a Journal of Chinese Universities},
year = {2006},
volume = {15},
number = {1},
pages = {60--66},
abstract = {
A real $n\times n$ symmetric matrix $X=(x_{ij})_{n \times n}$ is
called a bisymmetric matrix if $x_{ij}=x_{n+1-j, n+1-i}$. Based on
the projection theorem, the canonical correlation decomposition and
the generalized singular value decomposition, a method useful for
finding the least-squares solutions of the matrix equation
$A^{T}XA=B$ over bisymmetric matrices is proposed. The expression of
the least-squares solutions is given. Moreover, in the corresponding
solution set, the optimal approximate solution to a given matrix is
also derived. A numerical algorithm for finding the optimal
approximate solution is also described.},
issn = {},
doi = {https://doi.org/},
url = {http://global-sci.org/intro/article_detail/nm/10085.html}
}
TY - JOUR
T1 - Least-squares solutions of the equation AX=B over anti-Hermitian generalized Hamiltonian matrices
AU - Z. Zhang & C. Liu
JO - Numerical Mathematics, a Journal of Chinese Universities
VL - 1
SP - 60
EP - 66
PY - 2006
DA - 2006/02
SN - 15
DO - http://doi.org/
UR - https://global-sci.org/intro/article_detail/nm/10085.html
KW -
AB -
A real $n\times n$ symmetric matrix $X=(x_{ij})_{n \times n}$ is
called a bisymmetric matrix if $x_{ij}=x_{n+1-j, n+1-i}$. Based on
the projection theorem, the canonical correlation decomposition and
the generalized singular value decomposition, a method useful for
finding the least-squares solutions of the matrix equation
$A^{T}XA=B$ over bisymmetric matrices is proposed. The expression of
the least-squares solutions is given. Moreover, in the corresponding
solution set, the optimal approximate solution to a given matrix is
also derived. A numerical algorithm for finding the optimal
approximate solution is also described.
Z. Zhang and C. Liu. (2006). Least-squares solutions of the equation AX=B over anti-Hermitian generalized Hamiltonian matrices.
Numerical Mathematics, a Journal of Chinese Universities. 15 (1).
60-66.
doi:
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