Extending GCR Algorithm for the Least Squares Solutions on a Class of Sylvester Matrix Equations

Authors

  • Baohua Huang & Changfeng Ma

DOI:

https://doi.org/10.4208/nmtma.OA-2017-0010

Keywords:

Sylvester matrix equation, Least squares solution, Generalized conjugate residual algorithm, Numerical experiments.

Abstract

The purpose of this paper is to derive the generalized conjugate residual (GCR) algorithm for finding the least squares solution on a class of Sylvester matrix equations. We prove that if the system is inconsistent, the least squares solution can be obtained with infinite iterative steps in the absence of round-off errors. Furthermore, we provide a method for choosing the initial matrix to obtain the minimum norm least squares solutionof the problem. Finally, we give some numerical examples to illustrate the performance of GCR algorithm.

Published

2018-09-17

Issue

Section

Articles