AbstractWe develop normwise backward errors and condition numbers for the polynomial eigenvalue problem. The standard way of dealing with this problem is to reformulate it as a generalized eigenvalue problem (GEP). For the special case of the quadratic eigenvalue problem (QEP), we show that solving the QEP by applying the QZ algorithm to a corresponding GEP can be backward unstable. The QEP can be reformulated as a GEP in many ways. We investigate the sensitivity of a given eigenvalue to perturbations in each of the GEP formulations and identify which formulations are to be preferred for large and small eigenvalues, respectively
This work is a continuation of work by [J. L. Aurentz, T. Mach, R. Vandebril, and D. S. Watkins, J. ...
The most common way of solving the quadratic eigenvalue problem (QEP) (λ2M+λD+K)x = 0 is to convert ...
We present a chart of structured backward errors for approximate eigenpairs of singly and doubly str...
It is commonplace in many application domains to utilize polynomial eigenvalue problems to model the...
One of the most frequently used techniques to solve polynomial eigenvalue problems is linearization,...
In this thesis, we consider polynomial eigenvalue problems. We extend results on eigenvalue and eige...
SIGLEAvailable from British Library Document Supply Centre-DSC:6184.6725(no 332) / BLDSC - British L...
Backward errors and condition numbers are defined and evaluated for eigenvalues and eigenvectors of ...
We perform a backward error analysis of polynomial eigenvalue problems solved via linearization. Thr...
The most widely used approach for solving the polynomial eigenvalue problem $P(\lambda)x = \bigl(\su...
This article considers the backward error of the solution of polynomial eigenvalue problems expresse...
This article considers the backward error of the solution of polynomial eigenvalue problems expresse...
This report is a continuation of "Fast and backward stable computation of roots of polynomials" by J...
Backward error analyses of algorithms for solving polynomial eigenproblems can be "local" or "global...
We present a chart of structured backward errors for approximate eigenpairs of singly and doubly str...
This work is a continuation of work by [J. L. Aurentz, T. Mach, R. Vandebril, and D. S. Watkins, J. ...
The most common way of solving the quadratic eigenvalue problem (QEP) (λ2M+λD+K)x = 0 is to convert ...
We present a chart of structured backward errors for approximate eigenpairs of singly and doubly str...
It is commonplace in many application domains to utilize polynomial eigenvalue problems to model the...
One of the most frequently used techniques to solve polynomial eigenvalue problems is linearization,...
In this thesis, we consider polynomial eigenvalue problems. We extend results on eigenvalue and eige...
SIGLEAvailable from British Library Document Supply Centre-DSC:6184.6725(no 332) / BLDSC - British L...
Backward errors and condition numbers are defined and evaluated for eigenvalues and eigenvectors of ...
We perform a backward error analysis of polynomial eigenvalue problems solved via linearization. Thr...
The most widely used approach for solving the polynomial eigenvalue problem $P(\lambda)x = \bigl(\su...
This article considers the backward error of the solution of polynomial eigenvalue problems expresse...
This article considers the backward error of the solution of polynomial eigenvalue problems expresse...
This report is a continuation of "Fast and backward stable computation of roots of polynomials" by J...
Backward error analyses of algorithms for solving polynomial eigenproblems can be "local" or "global...
We present a chart of structured backward errors for approximate eigenpairs of singly and doubly str...
This work is a continuation of work by [J. L. Aurentz, T. Mach, R. Vandebril, and D. S. Watkins, J. ...
The most common way of solving the quadratic eigenvalue problem (QEP) (λ2M+λD+K)x = 0 is to convert ...
We present a chart of structured backward errors for approximate eigenpairs of singly and doubly str...