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Parameter Estimation and Inverse Problems

Autor Richard C. Aster, Brian Borchers, Clifford H. Thurber
en Limba Engleză Paperback – 22 oct 2018
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.


  • Features examples that are illustrated with simple, easy to follow problems that illuminate the details of a particular numerical method
  • Includes an online instructor’s guide that helps professors teach and customize exercises and select homework problems
  • Covers updated information on adjoint methods that are presented in an accessible manner
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Specificații

ISBN-13: 9780128046517
ISBN-10: 0128046511
Pagini: 404
Dimensiuni: 191 x 235 mm
Greutate: 0.69 kg
Ediția:3
Editura: ELSEVIER SCIENCE

Cuprins

1. Introduction2. Linear Regression3. Rank Deficiency and Ill-Conditioning4. Tikhonov Regularization5. Discretizing by Basis Functions6. Iterative Methods of Solving Linear Problems7. Additional Regularization Techniques8. Fourier Techniques9. Nonlinear Regression10. Nonlinear Inverse Problems11. Bayesian Methods12 Adjoint Methods

Recenzii

"A few years ago, it was my pleasure to review for the TLE this book’s first edition, published in 2005…The present revised version is some 60 pages longer and contains several significant modifications. As is true of the original, the book continues to be one of the clearest as well as the most comprehensive elementary expositions of discrete geophysical inverse theory. It is ideally suited for beginners as well as a fine resource for those searching for a particular inverse problem. Each algorithm is presented in the form of pseudo-code, then backed up by a collection of MATLAB codes downloadable from an Elsevier Web site…All examples in the book are beautifully illustrated with simple, easy to follow "cartoon" problems, and all painstakingly designed to illuminate the details of a particular numerical method." --The Leading Edge, July 2012