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Newton Methods for Nonlinear Problems

Name: Newton Methods for Nonlinear Problems
Brand: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
SKU: 9783642059278
Price: 465.24 PLN
Availability: InStock

Affine Invariance and Adaptive Algorithms

Autor: Peter Deuflhard

Język:

Oprawa: Miękka

Wydawca: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG

Dostępność: Dostępna u dostawcy

Wysyłamy za 5-8 dni

465.24 zł

This book deals with the efficient numerical solution of challenging nonlinear problems in science a...

Informacje o książce

Autor

Peter Deuflhard

Język

Angielski

Oprawa

Książka - Miękka

Data wydania

2010

strony

424

EAN

9783642059278

ISBN

3642059279

Enbook ID

05281006

Wydawca

Springer-Verlag Berlin and Heidelberg GmbH & Co. KG

Waga

670

Wymiary

168 x 25 x 24

Pełny opis

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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