Strong linearizations of rational matrices with polynomial part expressed in an orthogonal basis
DOI10.1016/j.laa.2019.02.003zbMath1416.65095arXiv1806.10544OpenAlexW2962817835WikidataQ128491114 ScholiaQ128491114MaRDI QIDQ2418992
María C. Quintana, S. Marcaida, Froilán M. Dopico
Publication date: 29 May 2019
Published in: Linear Algebra and its Applications (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1806.10544
rational matrixstrong linearizationrational eigenvalue problemrecovery of eigenvectorsHermitian strong linearizationstrong block minimal bases pencilsymmetric strong linearization
Numerical computation of eigenvalues and eigenvectors of matrices (65F15) Eigenvalue problems (93B60) Linearizations (93B18) Minimal systems representations (93B20) Eigenvalues, singular values, and eigenvectors (15A18) Matrices over function rings in one or more variables (15A54) Matrix pencils (15A22)
Related Items (8)
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Spectral equivalence of matrix polynomials and the index sum theorem
- Fast projection methods for minimal design problems in linear system theory
- Block Kronecker linearizations of matrix polynomials and their backward errors
- A block-symmetric linearization of odd degree matrix polynomials with optimal eigenvalue condition number and backward error
- A simplified approach to Fiedler-like pencils via block minimal bases pencils
- On vector spaces of linearizations for matrix polynomials in orthogonal bases
- Linearizations for Rational Matrix Functions and Rosenbrock System Polynomials
- Vector Spaces of Linearizations for Matrix Polynomials: A Bivariate Polynomial Approach
- Solving Rational Eigenvalue Problems via Linearization
- A compact rational Krylov method for large‐scale rational eigenvalue problems
- Minimal Bases of Rational Vector Spaces, with Applications to Multivariable Linear Systems
- Finite and infinite structures of rational matrices: a local approach
- Linearization of matrix polynomials expressed in polynomial bases
- Strong Linearizations of Rational Matrices
- The nonlinear eigenvalue problem
- Structured backward error analysis of linearized structured polynomial eigenvalue problems
- Nonlinear eigenvalue problems: a challenge for modern eigenvalue methods
- NLEIGS: A Class of Fully Rational Krylov Methods for Nonlinear Eigenvalue Problems
- Compact Rational Krylov Methods for Nonlinear Eigenvalue Problems
- Vector Spaces of Linearizations for Matrix Polynomials
- Symmetric Linearizations for Matrix Polynomials
- Memory-efficient Arnoldi algorithms for linearizations of matrix polynomials in Chebyshev basis
- Approximation of Large-Scale Dynamical Systems
This page was built for publication: Strong linearizations of rational matrices with polynomial part expressed in an orthogonal basis