Geophysical Data Analysis - Discrete Inverse Theory - Menke William
- 4th edition
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Présentation Geophysical Data Analysis - Discrete Inverse Theory de Menke William Format Grand format
- Livre Anglais loisir
Résumé :
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.
Biographie:
Dr. William Menke is an expert in geophysical and environmental data analysis and has written over one hundred peer-reviewed journal articles on these and related subjects. This fourth edition is a revision of the very well-received previous editions. His research focuses on the development of data analysis algorithms for time series analysis and imaging in the earth and environmental sciences and the application of these methods to volcanoes, earthquakes, and other natural hazards.
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