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Newton Methods for Nonlinear Problems: Affine Invariance and Adaptive Algorithms 2004. Corr. 2nd Edition
Contributor(s): Deuflhard, Peter (Author)
ISBN: 3540210997     ISBN-13: 9783540210993
Publisher: Springer
OUR PRICE:   $113.99  
Product Type: Hardcover - Other Formats
Published: April 2004
Qty:
Annotation:

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.

Additional Information
BISAC Categories:
- Mathematics | Number Systems
- Computers | Computer Science
- Mathematics | Differential Equations - General
Dewey: 510.285
LCCN: 2004102666
Series: Springer Computational Mathematics
Physical Information: 1" H x 6.14" W x 9.21" (1.74 lbs) 424 pages
 
Descriptions, Reviews, Etc.
Publisher Description:

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.