By how much can Residual Minimization Accelerate the Convergence of Orthogonal Residual Methods?

0404252 - UIVT-O 20010076 RIV NL eng J - Journal Article
Gutknecht, M. H. - Rozložník, Miroslav
By how much can Residual Minimization Accelerate the Convergence of Orthogonal Residual Methods?
Numerical Algorithms. Roč. 27, - (2001), s. 189-213. ISSN 1017-1398. E-ISSN 1572-9265
R&D Projects: GA ČR GA201/98/P108
Institutional research plan: AV0Z1030915
Keywords : system of linear algebraic equations * iterative method * Krylov space method * conjugate gradient method * biconjugate gradient method * CG * CGNE * CGNR * CGS * FOM * GMRes * QMR * TFQMR * residual smoothing * MR smoothing * QMR smoothing
Subject RIV: BA - General Mathematics
Impact factor: 0.438, year: 2001

We estimate how much smaller the residuals or quasi-residuals of the minimizing methods can be compared to those of the corresponding Galerkin or Petrov-Galerkin method. By an interpretation of smoothing processes in coordinate space we deepen the understanding of some of the underlying relationships and introduce a unifying framework for minimal residual and quasi-residual smoothing.
Permanent Link: http://hdl.handle.net/11104/0124515