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
firstyear 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 selfcontained
way, is supplemented with data sets and MatLab scripts that can be
used as a data analysis tutorial.
