
Discrete Inverse Problems
Insight and Algorithms
Per Christian Hansen(Author)
Society for Industrial and Applied Mathematics (SIAM) (Publisher)
Published on 18. March 2010
Book
Paperback/Softback
226 pages
978-0-89871-696-2 (ISBN)
Description
This acclaimed book introduces the practical treatment of inverse problems by means of numerical methods, with a focus on basic mathematical and computational aspects. To solve inverse problems, it demonstrates that insight about them and algorithms go hand in hand. Discrete Inverse Problems includes a number of tutorial exercises that give the reader hands-on experience with the methods, and challenges associated with the treatment of inverse problems. It includes carefully constructed illustrative computed examples and figures that highlight the important issues in the theory and algorithms. This book is written for graduate students, researchers, and professionals in engineering and other areas that depend on solving inverse problems with noisy data. It aims to provide readers with enough background that they can solve simple inverse problems and read more advanced literature on the subject.
More details
Language
English
Place of publication
Philadelphia
United States
Target group
Professional and scholarly
Product notice
Paperback (trade)
Unsewn / adhesive bound
Dimensions
Height: 259 mm
Width: 177 mm
Thickness: 15 mm
Weight
422 gr
ISBN-13
978-0-89871-696-2 (9780898716962)
Schweitzer Classification
Person
Per Christian Hansen is Professor of Scientific Computing at the Technical University of Denmark. His publications include two other books on inverse problems, several MATLAB packages, and many papers on inverse problems, matrix computations, and signal processing.
Content
Preface; List of symbols; 1. Introduction and motivation; 2. Meet the Fredholm integral equation of the first kind; 3. Getting to business: discretizations of linear inverse problems; 4. Computational aspects: regularization methods; 5. Getting serious: choosing the regularization parameter; 6. Toward real-world problems: iterative regularization; 7. Regularization methods at work: solving real problems; 8. Beyond the 2-norm: the use of discrete smoothing norms; Appendix A. Linear algebra stuff; Appendix B. Symmetric Toeplitz-plus-Hankel matrices and the DCT; Appendix C. Early work on 'Tikhonov regularization'; Bibliography; Index.