An algorithm for constructing nonnegative matrices with prescribed real eigenvalues-Reference-Cited by-同舟云学术

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An algorithm for constructing nonnegative matrices with prescribed real eigenvalues

Published:2015-04 Issue: Volume:256 Page:582-590
ISSN:0096-3003
Container-title:Applied Mathematics and Computation
language:en
Short-container-title:Applied Mathematics and Computation

Author:

Lin Matthew M.

Publisher

Elsevier BV

Subject

Applied Mathematics,Computational Mathematics

Reference36 articles.

1. Nonnegative matrices, Wiley-Interscience Series in Discrete Mathematics and Optimization;Minc,1988

2. Nonnegative matrices in the mathematical sciences;Berman,1994

3. Nonnegative matrices and applications;Bapat,1997

4. Nonnegative matrices–old problems, new applications;Berman,2006

5. Nonnegative Matrix and Tensor Factorizations: Applications to Exploratory Multi-way Data Analysis and Blind Source Separation;Cichocki,2009

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1. A direct solution to the stochastic inverse eigenvalue problem for complex-valued eigenspectra;Linear Algebra and its Applications;2023-02

2. A Riemannian inexact Newton dogleg method for constructing a symmetric nonnegative matrix with prescribed spectrum;Numerical Algorithms;2022-08-04

3. A new constrained optimization model for solving the nonsymmetric stochastic inverse eigenvalue problem;Linear and Multilinear Algebra;2020-11-11

4. A Riemannian variant of the Fletcher-Reeves conjugate gradient method for stochastic inverse eigenvalue problems with partial eigendata;Numerical Linear Algebra with Applications;2018-10-25

5. A Riemannian inexact Newton-CG method for constructing a nonnegative matrix with prescribed realizable spectrum;Numerische Mathematik;2018-06-28

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