Le livre est actuellement en rupture de stock

Newton methods for nonlinear problems

Affine Invariance and Adaptive Algorithms

Auteurs

Peter Deuflhard

Évaluation du livre

4,0(1)Évaluer

Paramètres

En savoir plus sur le livre

This book deals with the efficient numerical solution of challenging nonlinear problems in science and engineering, both in finite dimension (algebraic systems) and in infinite dimension (ordinary and partial differential equations). Its focus is on local and global Newton methods for direct problems or Gauss-Newton methods for inverse problems. The term 'affine invariance' means that the presented algorithms and their convergence analysis are invariant under one out of four subclasses of affine transformations of the problem to be solved. Compared to traditional textbooks, the distinguishing affine invariance approach leads to shorter theorems and proofs and permits the construction of fully adaptive algorithms. Lots of numerical illustrations, comparison tables, and exercises make the text useful in computational mathematics classes. At the same time, the book opens many directions for possible future research.

Édition

Achat du livre

Newton methods for nonlinear problems, Peter Deuflhard

Langue
Année de publication: 2004

Nous vous informerons par e-mail dès que nous l’aurons retrouvé.

Modes de paiement

4,0

Très bien

1 Évaluations

Évaluer

Il manque plus que ton avis ici.

Titre: Newton methods for nonlinear problems
Sous-titre: Affine Invariance and Adaptive Algorithms
Langue: Anglais
Auteurs: Peter Deuflhard
Éditeur: Springer
Publié: 2004
ISBN10: 3540210997
ISBN13: 9783540210993
Séries: Springer series in computational mathematics
Mots clés: Mathématiques
Évaluation: 4 sur 5
Description: This book deals with the efficient numerical solution of challenging nonlinear problems in science and engineering, both in finite dimension (algebraic systems) and in infinite dimension (ordinary and partial differential equations). Its focus is on local and global Newton methods for direct problems or Gauss-Newton methods for inverse problems. The term 'affine invariance' means that the presented algorithms and their convergence analysis are invariant under one out of four subclasses of affine transformations of the problem to be solved. Compared to traditional textbooks, the distinguishing affine invariance approach leads to shorter theorems and proofs and permits the construction of fully adaptive algorithms. Lots of numerical illustrations, comparison tables, and exercises make the text useful in computational mathematics classes. At the same time, the book opens many directions for possible future research.