Browsing by Autor "Hans Nina"

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Nonnegative generalized doubly stochastic matrices with prescribed elementary divisors
(2015) Ricardo L. Soto; Elvis Valero; Mario Salas; Hans Nina
This paper provides sufficient conditions for the existence of nonnegative generalized doubly stochastic matrices with prescribed elementary divisors. These results improve previous results and the constructive nature of their proofs allows for the computation of a solution matrix. In particular, this paper shows how to transform a generalized stochastic matrix into a nonnegative generalized doubly stochastic matrix, at the expense of increasing the Perron eigenvalue, but keeping other elementary divisors unchanged. Under certain restrictions, nonnegative generalized doubly stochastic matrices can be constructed, with spectrum \Lambda = {\lambda_1,\lambda_2 2, . . . , \lambda_n} for each Jordan canonical form associated with \Lambda
Nonnegative matrices with prescribed spectrum and elementary divisors
(Elsevier BV, 2013) Ricardo L. Soto; Roberto C. Dı́az; Hans Nina; Mario Salas
Realization of Extremal Spectral Data by Pentadiagonal Matrices
(Multidisciplinary Digital Publishing Institute, 2024) H. Pickmann-Soto; Silvia Finol Pérez; Charlie Lozano; Hans Nina
In this paper, we address the extremal inverse eigenvalue problem for pentadiagonal matrices. We provide sufficient conditions for their existence and realizability through new constructions that consider spectral data of its leading principal submatrices. Finally, we present some examples generated from the algorithmic procedures derived from our results.
The new inverse eigenvalue problems for periodic and generalized periodic Jacobi matrices from their extremal spectral data
(Elsevier BV, 2022) Silvia Finol Pérez; Charlie Lozano; Hans Nina; H. Pickmann-Soto; Jonnathan Rodríguez
Two Inverse Eigenproblems for Certain Symmetric and Nonsymmetric Pentadiagonal Matrices
(Multidisciplinary Digital Publishing Institute, 2022) Silvia Finol Pérez; Charlie Lozano; Hans Nina; H. Pickmann-Soto
In this paper, we give sufficient conditions for the construction of certain symmetric and nonsymmetric pentadiagonal matrices from particular spectral information. The construction of the symmetric pentadiagonal matrix considers the extreme eigenvalues of its leading principal submatrices and a prescribed entry, and the construction of the nonsymmetric pentadiagonal matrix also considers an eigenvector and two prescribed entries.