An extra-stabilized Morley finite element method (FEM) directly computes guaranteed lower eigenvalue bounds with optimal a priori convergence rates for the bi-Laplacian Dirichlet eigenvalues. The smallness assumption in 2D (resp., 3D) on maximal mesh-size makes computed th discrete bound . This holds multiple and clusters of eigenvalues serves localization eigenvalues, particular coarse meshes....

it is proved that by using bounds of eigenvalues of an interval matrix, someconditions for checking positive de niteness and stability of interval matricescan be presented. these conditions have been proved previously with variousmethods and now we provide some new proofs for them with a unity method.furthermore we introduce a new necessary and sucient condition for checkingstability of interv...

Recently, a novel flow for computing the eigenvectors associated with the smallest eigenvalues of a symmetric but not necessarily positive definite matrix was introduced. This meant that the eigenvectors associated with the smallest eigenvalues could be found simply by reversing the sign of the matrix. The current paper derives a cost function and the corresponding negative gradient flow which ...

In this paper we systematically derive a linear model for a n bus m machine system with nonlinear voltage dependent loads at the network buses. The model is versatile and can be used to study diierent phenomena such as steady state stability or voltage collapse. In addition to obtaining the system A matrix, we also obtain a transfer function between load voltages/angles and real/reactive powers...

We present and describe two new speaker adaptation methods which apply principal component analysis to maximum likelihood linear regression (MLLR). If we apply MLLR after transforming the baseline mean vectors by their eigenvectors, the contributions of these eigenvalues to the variance of the estimates for the MLLR matrix are inversely proportional to their corresponding eigenvalues. In the fi...

This paper gives the analysis and numerics underlying a shooting method for approximating the eigenvalues of nonselfadjoint Sturm-Liouville problems. We consider even order problems with (equally divided) separated boundary conditions. The method can nd the eigenvalues in a rectangle and in a left half-plane. It combines the argument principle with the compound matrix method (using the Magnus e...

In this paper, we consider the problem of efficiently computing the eigenvalues of limited-memory quasi-Newton matrices that exhibit a compact formulation. In addition, we produce a compact formula for quasi-Newton matrices generated by any member of the Broyden convex class of updates. Our proposed method makes use of efficient updates to the QR factorization that substantially reduces the cos...

This paper addresses the relative usefulness of Independent Component Analysis (ICA) for Face Recognition. Comparative assessments are made regarding (i) ICA sensitivity to the dimension of the space where it is carried out, and (ii) ICA discriminant performance alone or when combined with other discriminant criteria such as Bayesian framework or Fisher’s Linear Discriminant (FLD). Sensitivity ...