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Optimal Preconditioners of a Given Sparsity Pattern (Classic Reprint)

  • Couverture cartonnée
  • 42 Nombre de pages
Texte du rabat Excerpt from Optimal Preconditioners of a Given Sparsity PatternTo make this bound small, it should be close to 1. ... Lire la suite
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Texte du rabat

Excerpt from Optimal Preconditioners of a Given Sparsity Pattern

To make this bound small, it should be close to 1. This bound is sharp for the Chebyshev method, in the sense that there is an initial guess for which the bound will be attained at every step. It is not sharp for the conjugate gradient method. A sharp error bound for the conjugate gradient method is more complicated involving the distribution of all eigen values of m'la, but a condition number1 x(ma) close to 1 is sufficient to ensure fast con vergence of this algorithm as well, even when the effects of finite precision arithmetic are taken into account Therefore, we will define optimality in terms of the condition number k(m-1a) and minimization of this quantity will be our goal.

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Informations sur le produit

Titre: Optimal Preconditioners of a Given Sparsity Pattern (Classic Reprint)
Auteur:
Code EAN: 9781332173495
ISBN: 1332173497
Format: Couverture cartonnée
nombre de pages: 42
Poids: 72g
Taille: H229mm x B152mm x T2mm
Année: 2015

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