The Least-Norm Solution to a Matrix Equation over the Dual Quaterion Algebra

In this paper, we explore the least-norm solution to the classical matrix equation AXB=C over the dual quaternion algebra, where A, B, and C are given matrices, while X remains the unknown matrix. We begin by transforming the definition of the Frobenius norm for dual quaternion matrices into an equivalent form. Using this new expression, we investigate the least-norm solution to the equation AXB=C under solvability conditions. Additionally, we examine the minimum real part of the norm solution in cases where a least-norm solution does not exist. Finally, we provide two numerical examples to illustrate the main findings of our study.

Authors

Institutions

Publication Details

Journal
Symmetry
Published
2025-02-10
DOI
https://doi.org/10.3390/sym17020267
Citations
4
Primary Topic
Matrix Theory and Algorithms
Type
article
Field-Weighted Citation Impact
6.02

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The Least-Norm Solution to a Matrix Equation over the Dual Quaterion Algebra

L. Zhu, Qing‐Wen Wang, Zu-Liang Kou
4 citations
Symmetry
Matrix Theory and Algorithms
6.02
article

The Least-Norm Solution to a Matrix Equation over the Dual Quaterion Algebra

L. Zhu, Qing‐Wen Wang, Zu-Liang Kou
article en
4 citations

Abstract

In this paper, we explore the least-norm solution to the classical matrix equation AXB=C over the dual quaternion algebra, where A, B, and C are given matrices, while X remains the unknown matrix. We begin by transforming the definition of the Frobenius norm for dual quaternion matrices into an equivalent form. Using this new expression, we investigate the least-norm solution to the equation AXB=C under solvability conditions. Additionally, we examine the minimum real part of the norm solution in cases where a least-norm solution does not exist. Finally, we provide two numerical examples to illustrate the main findings of our study.

SymmetryVol. 17(2)
Shanghai University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 4%
Matrix Theory and Algorithms
6.02
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.