Iterative Hermitian R-conjugate solutions to general coupled sylvester matrix equations
Author(s) -
Shengkun Li
Publication year - 2017
Publication title -
filomat
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.449
H-Index - 34
eISSN - 2406-0933
pISSN - 0354-5180
DOI - 10.2298/fil1707061l
Subject(s) - hermitian matrix , mathematics , convergent matrix , matrix (chemical analysis) , conjugate , sylvester matrix , convergence (economics) , complex conjugate , conjugate gradient method , iterative method , symmetric matrix , mathematical analysis , pure mathematics , matrix function , mathematical optimization , polynomial matrix , physics , eigenvalues and eigenvectors , matrix polynomial , materials science , quantum mechanics , polynomial , economics , composite material , economic growth
For given symmetric orthogonal matrix $R$, i.e., $R^{T}=R$, $R^{2}=I$, a matrix $A\in \mathbb{C}^{n\times n}$ is termed Hermitian R-conjugate matrix if $A=A^{H}$, $RAR=\overline{A}$. In this paper, an iterative method is constructed for finding the Hermitian R-conjugate solutions of general coupled Sylvester matrix equations. Convergence analysis shows that the presented method is always convergent for any initial Hermitian R-conjugate matrix group for a loose restriction on the convergent factor. Meanwhile, the optimal convergent factor is also derived. Finally, two numerical examples are given to demonstrate the theoretical results and effectiveness.
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