Parameter Estimation and Inverse Problems

Parameter Estimation and Inverse Problems

4.25 (8 ratings by Goodreads)
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Parameter Estimation and Inverse Problems primarily serves as a textbook for advanced undergraduate and introductory graduate courses. It promotes a fundamental understanding of parameter estimation and inverse problem philosophy and methodology.

It introduces readers to Classical and Bayesian approaches to linear and nonlinear problems, with particular attention to computational, mathematical, and statistical issues related to their application to geophysical problems. Four appendices review foundational concepts in linear algebra, statistics, vector calculus, and notation. Pedagogy includes hundreds of highlighted equations, examples, and definitions; introductory chapter synopses; end-of-chapter exercises, both programming and theoretical; and suggestions for further reading.

The text is designed to be accessible to graduate students and professionals in physical sciences without an extensive mathematical background.
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Product details

  • Hardback | 320 pages
  • 195.6 x 223.5 x 25.4mm | 748.44g
  • Academic Press Inc
  • San Diego, United States
  • English
  • 0120656043
  • 9780120656042
  • 1,787,104

Review quote

"...a very useful textbook at undergraduate and graduate-level courses teaching the numerical techniques used in parameter estimation."
-Wojciech Debski, Institute of Geophysics, Polish Academy of Sciences

"...a 'one-shop-stop' for solving inverse problems; it contains many different methods for solving your particular problems and, in general, all of the background mathematics to help you understand the method itself."
-John Brittan, in THE LEADING EDGE, SEPT 2005

"The writing is uniformly clear....An exceptionally well written introductory text reasonably priced, placing it at least within reach of a college student."
-Sven Treitel, Leading Edge, March 2006

"Well designed...with a very clean approach [and] a fine introduction...The writing is conversational...that allows the ideas to come across clearly."
-Paul Phillips, University of Dallas for MAA, February 2006

"A well recommended addition to the technical library of anybody who has to deal with inverse problems."
--from John Brittan, Walton-on-Thames, UK for "The Leading Edge", September 2005
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Table of contents

1. Introduction
2. Linear Regression
3. Discretizing Continuous Inverse Problems
4. Rank Deficiency and Ill-Conditioning
5. Tikhonov Regularization
6. Iterative Methods
7. Other Regularization Techniques
8. Fourier Techniques
9. Nonlinear Regression
10. Nonlinear Inverse Problems
11. Bayesian Methods
Appendix A: Review of Linear Algebra
Appendix B: Review of Probability and Statistics
Appendix C: Glossary of Notation
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About Richard C. Aster

By Richard Aster, Brian Borchers and Cliff Thurber
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Rating details

8 ratings
4.25 out of 5 stars
5 38% (3)
4 50% (4)
3 12% (1)
2 0% (0)
1 0% (0)
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