矩阵方程的最小二乘{P,Q,k+1}-自反解

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  • School of Mathematics and Science, Hebei GEO University, Shijiazhuang, 050031, China; 
DONG Chang-zhou, male, native of Shijiazhuang, Hebei, associate professor of Hebei GEO University, engages in matrix algebra; LI Hao-xue (1996-), female, native of Handan, Hebei, master student of Hebei GEO University, engages in matrix algebra

收稿日期: 2022-03-25

  网络出版日期: 2022-10-10

基金资助

 Supported by the Education Department Foundation of Hebei Province ( Grant No.
QN2015218).

The Least Squares {P,Q,k+1}-Reflexive Solution to a Matrix Equation

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  •  School of Mathematics and Science, Hebei GEO University, Shijiazhuang, 050031, China; 
DONG Chang-zhou, male, native of Shijiazhuang, Hebei, associate professor of Hebei GEO University, engages in matrix algebra; LI Hao-xue (1996-), female, native of Handan, Hebei, master student of Hebei GEO University, engages in matrix algebra

Received date: 2022-03-25

  Online published: 2022-10-10

Supported by

 Supported by the Education Department Foundation of Hebei Province ( Grant No.
QN2015218).

摘要

 Let P ∈C m×m and Q∈C n×n be Hermitian and {k +1 } -potent matrices,
i.e., P k+1 = P = P , Q k+1 = Q = Q , where ( · ) ∗ stands for the conjugate transpose of a
matrix. A matrix X ∈C m×n is called {P,Q,k +1 } -reflexive (anti-reflexive) if PXQ = X
( PXQ = −X ). In this paper, the least squares solution of the matrix equation AXB = C
subject to {P,Q,k +1 } -reflexive and anti--reflexive constraints are studied by converting
into two simpler cases: k=1 and k=2.

本文引用格式

董昌州, 李浩雪 . 矩阵方程的最小二乘{P,Q,k+1}-自反解[J]. 数学季刊, 2023 , 38(2) : 210 -220 . DOI: 10.13371/j.cnki.chin.q.j.m.2023.02.008

Abstract

 Let P ∈C m×m and Q∈C n×n be Hermitian and {k +1 } -potent matrices,
i.e., P k+1 = P = P ∗ , Q k+1 = Q = Q ∗ , where ( · ) ∗ stands for the conjugate transpose of a
matrix. A matrix X ∈C m×n is called {P,Q,k +1 } -reflexive (anti-reflexive) if PXQ = X
( PXQ = −X ). In this paper, the least squares solution of the matrix equation AXB = C
subject to {P,Q,k +1 } -reflexive and anti--reflexive constraints are studied by converting
into two simpler cases: k=1 and k=2.
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