The Minimal Norm Least Squares Solutions for a Class of Matrix Equations

Volume 7, Issue 6, December 2022     |     PP. 132-138      |     PDF (210 K)    |     Pub. Date: December 11, 2022
DOI: 10.54647/mathematics11371    76 Downloads     5077 Views  

Author(s)

Jinrong Shen, College of Mathematics, Changsha University, Changsha 410003, China

Abstract
In this paper, the minimal norm least squares solution of matrix equations (AXC,BXD,AXD,BXC)=(E,F,G,H) is discussed, by using the projection theorem, the generalized singular value decomposition and the canonical correlation decomposition, the expression of the solution of this problem is obtained.

Keywords
Minium-norm least-square solution; the Generalized Singular Value Decomposition; the Canonical Correlation Decomposition; the Projection Theorem

Cite this paper
Jinrong Shen, The Minimal Norm Least Squares Solutions for a Class of Matrix Equations , SCIREA Journal of Mathematics. Volume 7, Issue 6, December 2022 | PP. 132-138. 10.54647/mathematics11371

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