Eigenvalue and eigenvector derivatives with respect to system design variables and their
applications have been and continue to be one of the core issues in the design, control and …

Numerical Linear Algebra and Applications, 2nd Edition: Back Matter Page 1 page 501 i i i i
Bibliography E. Anderson, Z. Bai, C. Bischof, S. Blackford, J. Demmel, J. Dongarra, J. Du …

We present a collection of 52 nonlinear eigenvalue problems in the form of a MATLAB
toolbox. The collection contains problems from models of real-life applications as well as …

We develop a novel technique through spectral decompositions to study the gravitational
perturbations of a black hole, without needing to decouple the linearized field equations into …

We develop a new algorithm for the computation of all the eigenvalues and optionally the
right and left eigenvectors of dense quadratic matrix polynomials. It incorporates scaling of …

Matrix polynomial eigenproblems arise in many application areas, both directly and as
approximations for more general nonlinear eigenproblems. One of the most common …

The most widely used approach for solving the polynomial eigenvalue problem
P(λ)x=(i=0^ml^iA_i)x=0 in n*n matrices A_i is to linearize to produce a larger order pencil …

A standard way of dealing with a matrix polynomial P(λ) is to convert it into an equivalent
matrix pencil—a process known as linearization. For any regular matrix polynomial, a new …

The first step when solving an infinite-dimensional eigenvalue problem is often to discretize
it. We show that one must be extremely careful when discretizing nonlinear eigenvalue …

We present numerical methods for model reduction in the numerical simulation of disk brake
squeal. Automotive disk brake squeal is a high frequency noise phenomenon based on self …