The Minimal Norm Least Squares Solutions for a Class of Matrix Equations
DOI: 10.54647/mathematics11371 76 Downloads 4476 Views
Author(s)
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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