Geophysical Data Analysis - Discrete Inverse Theory - Grand Format

Provides readers with the tools to make useful inferences from complicated data using inverse theory. Includes material on probability, including Bayesian influence, probability density function, and metropolis algorithm. Offers detailed discussion of the application of inverse theory to seismological, gravitational, and tectonic studies. Provides numerous examples, color figures, and end-of-chapter homework problems to help explore and further understand the presented ideas.
Includes MATLAB examples and problem sets. Geophysical Data Analysis, Fourth Edition, is a revised and expanded introduction to inverse theory and tomography as it is practiced by geophysicists. It demonstrates the methods needed to analyze a broad spectrum of geophysical datasets, with special attention 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.
This new edition includes expanded sections to cover material such as chi-squared tests, genetic algorithms, and adjoint methods, as well as a new appendix containing "crib sheets," which offer step-by-step summaries of methods presented. Utilizing problems and case studies along with MATLAB computer code and summaries of methods, Geophysical Data Analysis, Fourth Edition, provides data scientists and engineers in geophysics with the tools necessary to understand and apply mathematical techniques and inverse theory.