Geophysical Data Analysis: Discrete Inverse Theory

MATLAB edition


William Menke

Elsevier Inc., 2012, now available


Every student and researcher in the applied sciences who has analyzed data has practiced inverse theory. Inverse theory is simply the set of methods used to extract useful inferences about the world from physical measurements. The fitting of a straight line to data involves a simple application of inverse theory. Tomography, popularized by the physician’s CT and MRI scannesrs, uses it on a more sophisticated level. Being introductory in nature, this book deals only with “discrete inverse theory,” that is, the part of the theory concerned with parameters that either are truly discrete or can be adequately approximated as discrete. By adhering to these limitations, inverse theory can be presented on a level that is accessible to most first-year graduate students and many college seniors in the applied sciences. The only mathematics that is presumed is a working knowledge of the calculus and linear algebra and some familiarity with general concepts from probability theory and statistics. Nevertheless, the treatment is in no sense simplified. Realistic examples, drawn from the scientific literature, are used to illustrate the various techniques. Since in practice the solutions to most inverse problems require substantial computational effort, attention is given to how realistic problems can be solved. book, though written in a self-contained way, is supplemented with data sets and MatLab scripts that can be used as a data analysis tutorial.


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