205
Views
6
CrossRef citations to date
0
Altmetric
Research Article

An efficient method for least-squares problem of the quaternion matrix equation X - AX̂B = C

, , &
Pages 2569-2581 | Received 24 Feb 2020, Accepted 30 Jul 2020, Published online: 20 Aug 2020
 

ABSTRACT

In this paper, we consider the quaternion matrix equation XAXˆB=C, and study its minimal norm least squares solution, j-self-conjugate least-squares solution and anti-j-self-conjugate least-squares solution. By the real representation matrices of quaternion matrices, their particular structure and the properties of Frobenius norm, we convert above least-squares problems into corresponding problems of real matrix equations. The final results of the expressions only involve real matrices, and thus, the corresponding algorithms only involve real operations. Compared with the existing results, they are more convenient and efficient, which are also illustrated by the last two numerical examples.

2010 MATHEMATICS SUBJECT CLASSIFICATIONS:

Acknowledgments

The study was supported by the National Natural Science Foundation of China (No. 11801249) and the Scientific Research Foundation of Liaocheng University (No. 318011921).

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

The study was supported by the National Natural Science Foundation of China [No. 11801249] and the Scientific Research Foundation of Liaocheng University [No. 318011921].

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 670.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.