Geophysical Data Analysis and Inverse Theory with MATLAB® and Python

Author:   William Menke (Professor of Earth and Environmental Sciences ,Columbia University)
Publisher:   Elsevier Science Publishing Co Inc
Edition:   5th edition
ISBN:  

9780443137945


Pages:   342
Publication Date:   27 February 2024
Format:   Paperback
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Our Price $330.00 Quantity:  
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Geophysical Data Analysis and Inverse Theory with MATLAB® and Python


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Author:   William Menke (Professor of Earth and Environmental Sciences ,Columbia University)
Publisher:   Elsevier Science Publishing Co Inc
Imprint:   Academic Press Inc
Edition:   5th edition
Weight:   0.450kg
ISBN:  

9780443137945


ISBN 10:   0443137943
Pages:   342
Publication Date:   27 February 2024
Audience:   College/higher education ,  Tertiary & Higher Education
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

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

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Author Information

William Menke is a Professor of Earth and Environmental Sciences at Columbia University. 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. He has thirty years of experience teaching data analysis methods to both undergraduates and graduate students. Relevant courses that he has taught include, at the undergraduate level, Environmental Data Analysis and The Earth System, and at the graduate level, Geophysical Inverse Theory, Quantitative Methods of Data Analysis, Geophysical Theory and Practical Seismology.

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