Nearest matrix with prescribed eigenvalues and its applications
From MaRDI portal
Publication:908369
DOI10.1016/j.cam.2015.11.031zbMath1331.65067arXiv1401.0482OpenAlexW1507586232MaRDI QIDQ908369
Publication date: 4 February 2016
Published in: Journal of Computational and Applied Mathematics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1401.0482
Numerical computation of eigenvalues and eigenvectors of matrices (65F15) Eigenvalues, singular values, and eigenvectors (15A18) Numerical computation of matrix norms, conditioning, scaling (65F35)
Related Items (5)
Nearest linearly structured polynomial matrix with some prescribed distinct eigenvalues ⋮ On the distance from a matrix polynomial to matrix polynomials with some prescribed eigenvalues ⋮ Perturbation analysis on matrix pencils for two specified eigenpairs of a semisimple eigenvalue with multiplicity two ⋮ On the distance from a matrix polynomial to matrix polynomials with k prescribed distinct eigenvalues ⋮ Distance evaluation to the set of matrices with multiple eigenvalues
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Locating a nearest matrix with an eigenvalue of prespecified algebraic multiplicity
- Periodic orbits and chaos in fast-slow systems with Bogdanov-Takens type fold points
- Low rank approximation. Algorithms, implementation, applications
- On neighbouring matrices with quadratic elementary divisors
- On a remarkable implication of Malyshev's formula
- Computational aspect to the nearest matrix with two prescribed eigenvalues
- On condition numbers and the distance to the nearest ill-posed problem
- Asymptotic methods for relaxation oscillations and applications
- Geometric singular perturbation theory for ordinary differential equations
- Weakly connected neural networks
- Nearest matrix with two prescribed eigenvalues
- A formula for the 2-norm distance from a matrix to the set of matrices with multiple eigenvalues
- Structured low rank approximation
- On the distance to the closest matrix with triple zero eigenvalue
- Fixing multiple eigenvalues by a minimal perturbation
- Structured low-rank approximation and its applications
- Properties of a matrix with a very ill-conditioned eigenproblem
- Note on matrices with a very ill-conditioned eigenproblem
- Fixing two eigenvalues by a minimal perturbation
- Structured inverse eigenvalue problems
- Application of structured total least squares for system identification and model reduction
This page was built for publication: Nearest matrix with prescribed eigenvalues and its applications
