Geophysical Data Analysis: Discrete Inverse Theory
eBook - PDF

Geophysical Data Analysis: Discrete Inverse Theory

  1. 272 pages
  2. English
  3. PDF
  4. Available on iOS & Android
eBook - PDF

Geophysical Data Analysis: Discrete Inverse Theory

About this book

Geophysical Data Analysis: Discrete Inverse Theory is an introductory text focusing on discrete inverse theory that is concerned with parameters that either are truly discrete or can be adequately approximated as discrete. Organized into 12 chapters, the book's opening chapters provide a general background of inverse problems and their corresponding solution, as well as some of the basic concepts from probability theory that are applied throughout the text. Chapters 3-7 discuss the solution of the canonical inverse problem, that is, the linear problem with Gaussian statistics, and discussions on problems that are non-Gaussian and nonlinear are covered in Chapters 8 and 9. Chapters 10-12 present examples of the use of inverse theory and a discussion on the numerical algorithms that must be employed to solve inverse problems on a computer. This book is of value to graduate students and many college seniors in the applied sciences.

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Yes, you can access Geophysical Data Analysis: Discrete Inverse Theory by William Menke in PDF and/or ePUB format, as well as other popular books in Physical Sciences & Geography. We have over one million books available in our catalogue for you to explore.

Information

Publisher
Academic Press
Year
2012
Print ISBN
9780124909205
eBook ISBN
9780323141284
Topic
Physical Sciences
Subtopic
Geography
Index
Geography

Table of contents

  1. Front Cover
  2. Geophysical Data Analysis: Discrete Inverse Theory
  3. Copyright Page
  4. Table of Contents
  5. PREFACE
  6. INTRODUCTION
  7. Chapter 1. DESCRIBING INVERSE PROBLEMS
  8. Chapter 2. SOME COMMENTS ON PROBABILITY THEORY
  9. Chapter 3. SOLUTION OF THE LINEAR,GAUSSIAN INVERSE PROBLEM, VIEWPOINT 1: THE LENGTH METHOD
  10. Chapter 4. SOLUTION OF THE LINEAR, GAUSSIAN INVERSE PROBLEM, VIEWPOINT 2: GENERALIZED INVERSES
  11. Chapter 5. SOLUTION OF THE LINEAR, GAUSSIAN INVERSE PROBLEM, VIEWPOINT 3: MAXIMUM LIKELIHOOD METHODS
  12. Chapter 6. NONUNIQUENESS AND LOCALIZED AVERAGES
  13. Chapter 7. APPLICATIONS OF VECTOR SPACES
  14. Chapter 8. LINEAR INVERSE PROBLEMS AND NON-GAUSSIAN DISTRIBUTIONS
  15. Chapter 9. NONLINEAR INVERSE PROBLEMS
  16. Chapter 10. FACTOR ANALYSIS
  17. Chapter 11. SAMPLE INVERSE PROBLEMS
  18. Chapter 12. NUMERICAL ALGORITHMS
  19. APPENDIX A: Implementing Constraints with Lagrange Multipliers
  20. APPENDIX B: Inverse Theory with Complex Quantities
  21. REFERENCES
  22. INDEX