A block-symmetric linearization of odd degree matrix polynomials with optimal eigenvalue condition number and backward error
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Publication:1616095
DOI10.1007/s10092-018-0273-4zbMath1416.65091OpenAlexW2884510252WikidataQ114228551 ScholiaQ114228551MaRDI QIDQ1616095
Publication date: 31 October 2018
Published in: Calcolo (Search for Journal in Brave)
Full work available at URL: http://hdl.handle.net/10016/32176
eigenvaluelinearizationeigenvectormatrix polynomialstrong linearizationbackward error of an approximate eigenpairblock-symmetric linearizationconditioning of an eigenvalue
Numerical computation of eigenvalues and eigenvectors of matrices (65F15) Numerical computation of matrix norms, conditioning, scaling (65F35) Matrices over function rings in one or more variables (15A54)
Related Items (10)
Structured strong $\boldsymbol{\ell}$-ifications for structured matrix polynomials in the monomial basis ⋮ Unnamed Item ⋮ Strong linearizations of rational matrices with polynomial part expressed in an orthogonal basis ⋮ The infinite Lanczos method for symmetric nonlinear eigenvalue problems ⋮ A comparison of eigenvalue condition numbers for matrix polynomials ⋮ Factoring Block Fiedler Companion Matrices ⋮ Conditioning and backward errors of eigenvalues of homogeneous matrix polynomials under Möbius transformations ⋮ Backward error and conditioning of Fiedler companion linearizations ⋮ Explicit block-structures for block-symmetric Fiedler-like pencils ⋮ On why using \(\mathbb{DL}(P)\) for the symmetric polynomial eigenvalue problem might need to be reconsidered
Uses Software
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