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Parameter Estimation and Inverse Problems

ISBN-10: 0123850487
ISBN-13: 9780123850485
Edition: 2nd 2012
List price: $60.99
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Description: Parameter Estimation and Inverse Problems, 2e provides geoscience students and professionals with answers to common questions like how one can derive a physical model from a finite set of observations containing errors, and how one may determine the  More...

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Book details

List price: $60.99
Edition: 2nd
Copyright year: 2012
Publisher: Elsevier Science & Technology
Publication date: 2/22/2012
Binding: Hardcover
Pages: 376
Size: 7.75" wide x 10.00" long x 1.00" tall
Weight: 1.628
Language: English

Parameter Estimation and Inverse Problems, 2e provides geoscience students and professionals with answers to common questions like how one can derive a physical model from a finite set of observations containing errors, and how one may determine the quality of such a model. This book takes on these fundamental and challenging problems, introducing students and professionals to the broad range of approaches that lie in the realm of inverse theory. The authors present both the underlying theory and practical algorithms for solving inverse problems. The authors' treatment is appropriate for geoscience graduate students and advanced undergraduates with a basic working knowledge of calculus, linear algebra, and statistics.Parameter Estimation and Inverse Problems, 2e  introduces readers to both Classical and Bayesian approaches to linear and nonlinear problems with particular attention paid to computational, mathematical, and statistical issues related to their application to geophysical problems. The textbook includes Appendices covering essential linear algebra, statistics, and notation in the context of the subject. A companion website features computational examples (including all examples contained in the textbook) and useful subroutines using MATLAB.Includes appendices for review of needed concepts in linear, statistics, and vector calculus.Companion website contains comprehensive MATLAB code for all examples, which readers can reproduce, experiment with, and modify.Online instructor's guide helps professors teach, customize exercises, and select homework problemsAccessible to students and professionals without a highly specialized mathematical background.

Preface
Introduction
Linear Regression
Rank Deficiency and Ill Conditioning
Tikhonov Regularization
Discretizing Inverse Problems Using Basis Functions
Iterative Methods
Additional Regularization Techniques
Fourier Techniques
Nonlinear Regression
Nonlinear Inverse Problems
Bayesian Methods
Epilogue
Review of Linear Algebra
Review of Probability and Statistics
Review of Vector Calculus
Glossary of Notation
Bibliography
Index

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