Geophysical Data Analysis: Discrete Inverse Theory, 3rd Edition

Key Features

• Additional material on probability, including Bayesian influence, probability density function, and metropolis algorithm
• Detailed discussion of application of inverse theory to tectonic, gravitational and geomagnetic studies
• Numerous examples and end-of-chapter homework problems help you explore and further understand the ideas presented
• Use as classroom text facilitated by a complete set of exemplary lectures in Microsoft PowerPoint format and homework problem solutions for instructors
• Check out the companion website: http://www.elsevierdirect.com/companion.jsp?ISBN=9780123971609
  and the Instructor website: http://textbooks.elsevier.com/web/manuals.aspx?isbn=9780123971609

Description

Since 1984, Geophysical Data Analysis has filled the need for a short, concise reference on inverse theory for individuals who have an intermediate background in science and mathematics. The new edition maintains the accessible and succinct manner for which it is known, with the addition of:

• MATLAB examples and problem sets
• Advanced color graphics
• Coverage of new topics, including Adjoint Methods; Inversion by Steepest Descent, Monte Carlo and Simulated Annealing methods; and Bootstrap algorithm for determining empirical confidence intervals
• Online data sets and MATLAB scripts that can be used as an inverse theory tutorial.

Readership

Graduate students and researchers in solid earth geophysics, seismology, atmospheric sciences and other areas of applied physics (e.g. image processing) and mathematics.

Geophysical Data Analysis: Discrete Inverse Theory, 3rd Edition

Preface
Introduction
Chapter 1: Describing Inverse Problems
Chapter 2: Some Comments on Probability Theory
Chapter 3: Solution of the Linear, Gaussian Inverse Problem, Viewpoint 1: The Length Method
Chapter 4: Solution of the Linear, Gaussian Inverse Problem, Viewpoint 2: Generalized Inverses
Chapter 5: Solution of the Linear, Gaussian Inverse Problem, Viewpoint 3: Maximum Likelihood Methods
Chapter 6: Nonuniqueness and Localized Averages
Chapter 7: Applications of Vector Spaces
Chapter 8: Linear Inverse Problems and Non-Gaussian Statistics
Chapter 9: Nonlinear Inverse Problems
Chapter 10: Factor Analysis
Chapter 11: Continuous Inverse Theory and Tomography
Chapter 12: Sample Inverse Problems
Chapter 13: Applications of Inverse Theory to Solid Earth Geophysics
Appendices