Steplength optimization and linear multigrid methods.
Stochastic Arithmetic Theory and Experiments
Stochastic arithmetic has been developed as a model for exact computing with imprecise data. Stochastic arithmetic provides confidence intervals for the numerical results and can be implemented in any existing numerical software by redefining types of the variables and overloading the operators on them. Here some properties of stochastic arithmetic are further investigated and applied to the computation of inner products and the solution to linear systems. Several numerical experiments are performed showing...
Strang-type preconditioners for solving systems of ODEs by boundary value methods.
Strict Chebyshev Approximation for General Systems of Linear Equations.
Strong rank revealing Cholesky factorization.
Strong Underrelaxation in Kaczmarz's Method for Inconsistent Systems
Strong Uniqueness. A Far-Reaching Criterion for the Convergence Analysis of Iterative Procedures.
Structure preserving algorithms for perplectic eigenproblems.
Structured condition numbers and backward errors in scalar product spaces.
Structured conditioning of matrix functions.
Structured low rank approximations of the sylvester resultant matrix for approximate GCDS of Bernstein basis polynomials.
Structured polynomial eigenproblems related to time-delay systems.
Structured QR algorithms for Hamiltonian symmetric matrices.
Structured tools for structured matrices.
Sturm-Liouville difference equations and banded matrices
Subdirect sums of doubly diagonally dominant matrices.
Subdirect sums of -strictly diagonally dominant matrices.
Superlinear CG convergence for special right-hand sides.
Sur la réduction des déterminants des matrices de Jacobi d'un type spécial avec l'application à la recherche de leurs valeurs propres
Sur le calcul des produits de matrices.