Many advances in the development of Krylov subspace methods for the iterative solution of
linear systems during the last decade and a half are reviewed. These new developments …

Recently, the authors proposed a new Krylov subspace iteration, the quasi-minimal residual
(QMR) algorithm, for solving non-Hermitian linear systems. In the original implementation of …

1. INTRODUCTION. We explain why Krylov methods make sense, and why it is natural to
represent a solution to a linear system as a member of a Krylov space. In particular we show …

We consider the behavior of the GMRES method for solving a linear system Ax=b when A is
singular or nearly so, ie, ill conditioned. The (near) singularity of A may or may not affect the …

treated in more detail. They are just specimen of larger classes of schemes. Es sentially, we
have to distinguish between semi-analytical methods, discretiza tion methods, and lumped …

Solving systems of algebraic linear equations is among the most frequent problems in
scientific computing. It appears in many areas like physics, engineering, chemistry, biology …

Usually generalized least squares problems are solved by transforming them into regular
least squares problems which can then be solved by well-known numerical methods …

Simulating deformable objects based on physical laws has become the most popular
technique for modeling textiles, skin, or volumetric soft objects like human tissue. The …

Physically based modelling of deformable objects has become the most popular technique
to model textiles, skin or human tissue. The crucial problem in the animation of deformable …

An index splitting of a singular matrix A for the Drazin inverse and its relative iterations for
the minimal P-norm solution of the singular linear system Ax= b [b∈ R (A k), k= Ind (A)] are …