SIAMMAX
2010
13 years 6 months ago
2010
This article presents rigorous normwise perturbation bounds for the Cholesky, LU and QR factorizations with normwise or componentwise perturbations in the given matrix. The conside...
SIAMMAX
2010
13 years 6 months ago
2010
We investigate the structural, spectral, and sparsity properties of Stochastic Galerkin matrices as they arise in the discretization of linear differential equations with random co...
SIAMMAX
2010
13 years 6 months ago
2010
The main goal of this paper is to develop a numerical procedure for construction of covariance matrices such that for a given covariance structural model and a discrepancy function...
SIAMMAX
2010
13 years 6 months ago
2010
The aim of the paper is to provide a theoretical basis for approximate reduced SQP methods. In contrast to inexact reduced SQP methods, the forward and the adjoint problem accuraci...
SIAMMAX
2010
13 years 6 months ago
2010
Many mathematical models involve flow equations characterized by nonconstant viscosity, and a Stokes type problem with variable viscosity coefficient arises. Appropriate block diag...
SIAMMAX
2010
13 years 6 months ago
2010
We propose a new approach to estimate the joint spectral radius and the joint spectral subradius of an arbitrary set of matrices. We first restrict our attention to matrices that ...
SIAMMAX
2010
13 years 6 months ago
2010
SIAMMAX
2010
13 years 6 months ago
2010
Abstract. Given a symmetric positive definite matrix A, we compute a structured approximate Cholesky factorization A RT R up to any desired accuracy, where R is an upper triangula...
SIAMMAX
2010
13 years 6 months ago
2010
The problem of completing a low-rank matrix from a subset of its entries is often encountered in the analysis of incomplete data sets exhibiting an underlying factor model with app...
SIAMMAX
2010
13 years 6 months ago
2010
The mth Chebyshev polynomial of a square matrix A is the monic polynomial that minimizes the matrix 2-norm of p(A) over all monic polynomials p(z) of degree m. This polynomial is u...