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Parameter estimation and inverse problems

By: Aster, Richard C.
Contributor(s): Borchers, Brian [Co author] | Thurber, Clifford H [Co author].
Material type: materialTypeLabelBookPublisher: Cambridge Elsevier 2019Edition: 3rd.Description: xi, 392p. With index.ISBN: 9780128046517.Subject(s): Mathematical models | Parameter estimation | Inverse problems | GeophysicsDDC classification: 515.357 Summary: Parameter Estimation and Inverse Problems, Third Edition, is structured around a course at New Mexico Tech and is designed to be accessible to typical graduate students in the physical sciences who do not have an extensive mathematical background. The book is complemented by a companion website that includes MATLAB codes that correspond to examples that are illustrated with simple, easy to follow problems that illuminate the details of particular numerical methods. Updates to the new edition include more discussions of Laplacian smoothing, an expansion of basis function exercises, the addition of stochastic descent, an improved presentation of Fourier methods and exercises, and more. https://www.elsevier.com/books/parameter-estimation-and-inverse-problems/aster/978-0-12-804651-7
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Slot 1376 (0 Floor, East Wing) Non-fiction 515.357 A8P2 (Browse shelf) Available 198805

Table of Contents
1. Introduction
2. Linear Regression
3. Rank Deficiency and Ill-Conditioning
4. Tikhonov Regularization
5. Discretizing by Basis Functions
6. Iterative Methods of Solving Linear Problems
7. Additional Regularization Techniques
8. Fourier Techniques
9. Nonlinear Regression
10. Nonlinear Inverse Problems
11. Bayesian Methods
12 Adjoint Methods

Parameter Estimation and Inverse Problems, Third Edition, is structured around a course at New Mexico Tech and is designed to be accessible to typical graduate students in the physical sciences who do not have an extensive mathematical background. The book is complemented by a companion website that includes MATLAB codes that correspond to examples that are illustrated with simple, easy to follow problems that illuminate the details of particular numerical methods. Updates to the new edition include more discussions of Laplacian smoothing, an expansion of basis function exercises, the addition of stochastic descent, an improved presentation of Fourier methods and exercises, and more.

https://www.elsevier.com/books/parameter-estimation-and-inverse-problems/aster/978-0-12-804651-7

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