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Parameter Estimation and Inverse Problems
- 3rd Edition - October 16, 2018
- Authors: Richard C. Aster, Brian Borchers, Clifford H. Thurber
- Language: English
- Paperback ISBN:9 7 8 - 0 - 1 2 - 8 0 4 6 5 1 - 7
- eBook ISBN:9 7 8 - 0 - 1 2 - 8 1 3 4 2 3 - 8
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 ph… Read more
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Request a sales quoteParameter 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
Graduate and advanced undergraduate students taking courses in geophysical inverse problems. It is also used as a reference for geoscientists and researchers in academe and industry
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
- No. of pages: 404
- Language: English
- Edition: 3
- Published: October 16, 2018
- Imprint: Elsevier
- Paperback ISBN: 9780128046517
- eBook ISBN: 9780128134238
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Richard C. Aster
Professor Aster is an Earth scientist with broad interests in geophysics, seismological imaging and source studies, and Earth processes. His work has included significant field research in western North America, Italy, and Antarctica. Professor Aster also has strong teaching and research interests in geophysical inverse and signal processing methods and is the lead author on the previous two editions. Aster was on the Seismological Society of America Board of Directors, 2008-2014 and won the IRIS Leadership Award, 2014.
Affiliations and expertise
New Mexico Institute of Mining and Technology, Socorro, USABB
Brian Borchers
Dr. Borchers’ primary research and teaching interests are in optimization and inverse problems. He teaches a number of undergraduate and graduate courses at NMT in linear programming, nonlinear programming, time series analysis, and geophysical inverse problems. Dr. Borchers’ research has focused on interior point methods for linear and semidefinite programming and applications of these techniques to combinatorial optimization problems. He has also done work on inverse problems in geophysics and hydrology using linear and nonlinear least squares and Tikhonov regularization.
Affiliations and expertise
New Mexico Institute of Mining and Technology, Socorro, USACT
Clifford H. Thurber
Professor Thurber is an international leader in research on three-dimensional seismic imaging ("seismic tomography") using earthquakes. His primary research interests are in the application of seismic tomography to fault zones, volcanoes, and subduction zones, with a long-term focus on the San Andreas fault in central California and volcanoes in Hawaii and Alaska. Other areas of expertise include earthquake location (the topic of a book he edited) and geophysical inverse theory.
Affiliations and expertise
University of Wisconsin-Madison, USARead Parameter Estimation and Inverse Problems on ScienceDirect