Computing matrix symmetrizers. II: New methods using eigendata and linear means; a comparison.

DOI10.1016/j.laa.2015.06.031zbMath1337.65030OpenAlexW824953440MaRDI QIDQ286181

Frank Uhlig, Froilán M. Dopico

Publication date: 20 May 2016

Published in: Linear Algebra and its Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.laa.2015.06.031

zbMATH Keywords

linear equationsymmetrizernumerical algorithmeigenvalue method\texttt{MATLAB} codematrix optimizationprincipal subspace computationsymmetric matrix factorizationsymmetrizer computation

Mathematics Subject Classification ID

Factorization of matrices (15A23) Hermitian, skew-Hermitian, and related matrices (15B57) Iterative numerical methods for linear systems (65F10) Numerical solutions to equations with linear operators (65J10)

Related Items (3)

Computation of large-dimension Jordan normal transform via popular platforms ⋮ Unnamed Item ⋮ A two-level iterative scheme for general sparse linear systems based on approximate skew-symmetrizers

Uses Software

• LAPACK
• Matlab
• mctoolbox
• HQR3 EXCHNG

Cites Work

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• On Symmetrizable Systems of Second Kind
• Dynamics of Symmetrizable Nonconservative Systems
• LAPACK Users' Guide
• An Algorithm for Numerical Computation of the Jordan Normal Form of a Complex Matrix
• Ill-Conditioned Eigensystems and the Computation of the Jordan Canonical Form
• Taussky's theorem, symmetrizability and modal analysis revisited
• Accuracy and Stability of Numerical Algorithms
• On a method of solving the complete eigenvalue problem for a degenerate matrix
• Computing Eigenvalues of Complex Matrices by Determinant Evaluation and by Methods of Danilewski and Wielandt
• An algorithm for numerical determination of the structure of a general matrix
• The principle of minimized iterations in the solution of the matrix eigenvalue problem

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