A note on the $\top$-Stein matrix equation

TL;DR

This paper investigates the $ op$-Stein matrix equation, establishing conditions for unique solutions, exploring its connection to eigenvalue problems, and discussing numerical methods, residuals, backward errors, and perturbation bounds.

Contribution

It provides necessary and sufficient conditions for unique solvability and links the equation to generalized eigenvalue theory, along with numerical solution insights.

Findings

Conditions for unique solvability are established.

A relationship between the matrix equation and eigenvalue problems is shown.

Perturbation bounds and residual analysis are provided.

Abstract

This note is concerned with the linear matrix equation $X = AX^\top B + C$, where the operator $(\cdot)^\top$ denotes the transpose ($\top$) of a matrix. The first part of this paper set forth the necessary and sufficient conditions for the unique solvability of the solution $X$. The second part of this paper aims to provide a comprehensive treatment of the relationship between the theory of the generalized eigenvalue problem and the theory of the linear matrix equation. In the finally part of this paper starts with a briefly review of numerical methods for solving the linear matrix equation. Related to the computed methods, knowledge of the residual is discussed. An expression related to the backward error of an approximate solution is obtained; it shows that a small backward error implies a small residual. Just like for the discussion of linear matrix equations, perturbation bounds for solving the linear matrix equation are also proposed in this work.