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Könyv Newton Methods for Nonlinear Problems Peter Deuflhard

Newton Methods for Nonlinear Problems

Affine Invariance and Adaptive Algorithms

Szerző: Peter Deuflhard
Nyelv: Angol
Kötés: Puha kötésű
Kiadó: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Elérhetőség: Beszállítói készleten
Küldés 5-8 napon belül
42 378 Ft
This book deals with the efficient numerical solution of challenging nonlinear problems in science a...

Információk a könyvről

Szerző
Peter Deuflhard
Nyelv
Angol
Kötés
Könyv - Puha kötésű
Kiadva
2010
oldal
424
EAN
9783642059278
ISBN
3642059279
Enbook ID
05281006
Kiadó
Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Súly
670
Méretek
168 x 25 x 24

Teljes leírás

This book deals with the efficient numerical solution of challenging nonlinear problems in science and engineering, both in finite and in infinite dimension. Its focus is on local and global Newton methods for direct problems or Gauss-Newton methods for inverse problems. 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. 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.

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