Newton Methods for Nonlinear Problems
Affine Invariance and Adaptive Algorithms
Series: Springer Series in Computational Mathematics; 35;
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Product details:
- Edition number 2011
- Publisher Springer
- Date of Publication 16 September 2011
- Number of Volumes 1 pieces, Book
- ISBN 9783642238987
- Binding Paperback
- No. of pages424 pages
- Size 235x155 mm
- Weight 670 g
- Language English
- Illustrations 49 Illustrations, black & white 10
Categories
Short 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.
MoreLong 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.
From the reviews:
?This monograph covers a multitude of Newton methods and presents the algorithms and their convergence analysis from the perspective of affine invariance, which has been the subject of research by the author since 1970. ? The book is intended for graduate students of mathematics and computational science and also for researchers in the area of numerical analysis and scientific computing. ? As a research monograph, the book not only assembles the current state of the art, but also points to future research prospects.? (Gudula Runger, ACM Computing Reviews, June, 2012)
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