Generalized inverse eigenvalue problem for (P,Q)-conjugate matrices and the associated approximation problem

In this paper, the generalized inverse eigenvalue problem for the ( P , Q )-conjugate matrices and the associated approximation problem are discussed by using generalized singular value decomposition (GSVD). Moreover, the least residual problem of the above generalized inverse eigenvalue problem is...

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Bibliographic Details
Published inWuhan University journal of natural sciences Vol. 21; no. 2; pp. 93 - 98
Main Authors Dai, Lifang, Liang, Maolin
Format Journal Article
LanguageEnglish
Published Wuhan Wuhan University 01.04.2016
Springer Nature B.V
Subjects
Approximation
Biomedical and Life Sciences
Computer Science
Correlation analysis
Decomposition
Eigenvalues
Generalized inverse
Life Sciences
Materials Science
Mathematics
Singular value decomposition
least residual problem
O124.6
canonical correlation decomposition (CCD)
(
optimal approximation
,
conjugate matrices
generalized inverse eigenvalue problem
generalized singular value decomposition (GSVD)
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Summary:In this paper, the generalized inverse eigenvalue problem for the ( P , Q )-conjugate matrices and the associated approximation problem are discussed by using generalized singular value decomposition (GSVD). Moreover, the least residual problem of the above generalized inverse eigenvalue problem is studied by using the canonical correlation decomposition (CCD). The solutions to these problems are derived. Some numerical examples are given to illustrate the main results.
ISSN:1007-1202
1993-4998
DOI:10.1007/s11859-016-1143-z