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Statistical and Computational Inverse Problems

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Statistical and Computational Inverse Problems Synopsis

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 known.

About This Edition

ISBN: 9781441919649
Publication date:
Author: Jari Kaipio, Erkki Somersalo
Publisher: Springer an imprint of Springer New York
Format: Paperback
Pagination: 339 pages
Series: Applied Mathematical Sciences
Genres: Probability and statistics
Stochastics
Cybernetics and systems theory
Numerical analysis
Biomedical engineering
Calculus and mathematical analysis
Mathematical physics
Maths for engineers

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