This book is aimed at postgraduate students in applied mathematics as
well as at engineering and physics students with a ?rm background in
mathem- ics. The ?rst four chapters can be used as the material for a
?rst course on inverse problems with a focus on computational and
statistical aspects. On the other hand, Chapters 3 and 4, which discuss
statistical and nonstati- ary inversion methods, can be used by students
already having knowldege of classical inversion methods. There is rich
literature, including numerous textbooks, on the classical aspects of
inverse problems. From the numerical point of view, these books
concentrate on problems in which the measurement errors are either very
small or in which the error properties are known exactly. In real-world
pr- lems, however, the errors are seldom very small and their properties
in the deterministic sensearenot wellknown.For example,
inclassicalliteraturethe errornorm is usuallyassumed to be a known
realnumber. In reality, the error norm is a random variable whose mean
might be know