Parameter Estimation and Inverse Problems
Nonfiction, Science & Nature, Science, Earth Sciences, Geophysics, Geology
| Author: | Richard C. Aster, Brian Borchers, Clifford H. Thurber | ISBN: | 9780128134238 |
| Publisher: | Elsevier Science | Publication: | October 16, 2018 |
| Imprint: | Elsevier | Language: | English |
| Author: | Richard C. Aster, Brian Borchers, Clifford H. Thurber |
| ISBN: | 9780128134238 |
| Publisher: | Elsevier Science |
| Publication: | October 16, 2018 |
| Imprint: | Elsevier |
| Language: | English |
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
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
