Least-squares solutions of generalized inverse eigenvalue problem over Hermitian–Hamiltonian matrices with a submatrix constraint

In this paper, a gradient-based iterative algorithm is proposed for finding the least-squares solutions of the following constrained generalized inverse eigenvalue problem: given X ∈ C n × m , Λ = diag ( λ 1 , λ 2 , … , λ m ) ∈ C m × m , find A ∗ , B ∗ ∈ C n × n , such that ‖ A X - B X Λ ‖ is minimi...

Celý popis

Uloženo v:

Podrobná bibliografie
Vydáno v:	Computational & applied mathematics Ročník 37; číslo 1; s. 593 - 603
Hlavní autoři:	Cai, Jing, Chen, Jianlong
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Cham Springer International Publishing 01.03.2018 Springer Nature B.V
Témata:	Algorithms Applications of Mathematics Applied physics Computational mathematics Computational Mathematics and Numerical Analysis Eigenvalues Generalized inverse Iterative algorithms Iterative methods Least squares Mathematical Applications in Computer Science Mathematical Applications in the Physical Sciences Mathematics Mathematics and Statistics Matrix Roundoff error Hermitian–Hamiltonian matrix 65J22 Optimal approximation Submatrix constraint Generalized inverse eigenvalue problem 15A29
ISSN:	0101-8205, 2238-3603, 1807-0302
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!

Buďte první, kdo okomentuje tento záznam!