Geophysical Data Analysis and Inverse Theory with MATLAB or Python, Fifth Edition is a revised and expanded introduction to inverse theory and tomography as it is practiced by geophysicists. The book demonstrates the methods needed to analyze a broad spectrum of geophysical datasets, with special attention given to those methods that generate images of the earth. Data analysis can be a mathematically complex activity, but the treatment in this volume is carefully designed to emphasize those mathematical techniques that readers will find the most familiar and to systematically introduce less-familiar ones. A series of "crib sheets" offer step-by-step summaries of methods presented. Utilizing problems and case studies, along with MATLAB and Python computer code and summaries of methods, the book provides professional geophysicists, students, data scientists and engineers in geophysics with the tools necessary to understand and apply mathematical techniques and inverse theory.
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Table of Contents
1. Getting started with matlab� or python 2. Describing inverse problems 3. Using probabilty to describe random variation 4. Solution of the linear, normal inverse problem, viewpoint 1: the length method 5. Solution of the linear, normal inverse problem, viewpoint 2: generalized inverses 6. Solution of the linear, normal inverse problem, viewpoint 3: maximum likelihood methods 7. Data assimilation methods including gaussian process regression and kalman filtering 8. Nonuniqueness and localized averages 9. Applications of vector spaces 10. Linear inverse problems with non-normal statistics 11. Nonlinear inverse problems 12. Monte carlo methods 13. Factor analysis 14. Continuous inverse theory and tomography 15. Sample inverse problems 16. Applications of inverse theory to solid earth geophysics 17. Important algorithms and method summaries
