Bayesian Approach to Inverse Problems
Language: English
Published by Wiley Jun 2008, 2008
- Hardcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
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Condition: New
US$ 356.87
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Add to basketItem description from seller
Neuware - Many scientific, medical or engineering problems raise the issue of recovering some physical quantities from indirect measurements; for instance, detecting or quantifying flaws or cracks within a material from acoustic or electromagnetic measurements at its surface is an essential problem of non-destructive evaluation. The concept of inverse problems precisely originates from the idea of inverting the laws of physics to recover a quantity of interest from measurable data. Unfortunately, most inverse problems are ill-posed, which means that precise and stable solutions are not easy to devise. Regularization is the key concept to solve inverse problems. The goal of this book is to deal with inverse problems and regularized solutions using the Bayesian statistical tools, with a particular view to signal and image estimation. The first three chapters bring the theoretical notions that make it possible to cast inverse problems within a mathematical framework. The next three chapters address the fundamental inverse problem of deconvolution in a comprehensive manner. Chapters 7 and 8 deal with advanced statistical questions linked to image estimation. In the last five chapters, the main tools introduced in the previous chapters are put into a practical context in important applicative areas, such as astronomy or medical imaging.…
Seller Inventory # 9781848210325
- Title
- Bayesian Approach to Inverse Problems
- Author
- Jérôme Idier
- Publisher
- Wiley Jun 2008
- Publication year
- 2008
- Condition
- Neu
- Binding
- Buch
- Language
- English
- ISBN 10
- 1848210329
- ISBN 13
- 9781848210325
- Item weight
- 699 grams
- Dimensions
- 241x161x27 mm
Unfortunately, most inverse problems are ill-posed, which means that precise and stable solutions are not easy to devise. Regularization is the key concept to solve inverse problems.
The goal of this book is to deal with inverse problems and regularized solutions using the Bayesian statistical tools, with a particular view to signal and image estimation.
The first three chapters bring the theoretical notions that make it possible to cast inverse problems within a mathematical framework. The next three chapters address the fundamental inverse problem of deconvolution in a comprehensive manner. Chapters 7 and 8 deal with advanced statistical questions linked to image estimation. In the last five chapters, the main tools introduced in the previous chapters are put into a practical context in important applicative areas, such as astronomy or medical imaging.
"Synopsis" may belong to another edition of this title.
About the Author
His major scientific interest is in statistical approaches to inverse problems for signal and image processing. More specifically, he studies probabilistic modeling, inference and optimization issues yielded by data processing problems such as denoising, deconvolution, spectral analysis, reconstruction from projections. The investigated applications are mainly non destructive testing, astronomical imaging and biomedical signal processing, and also radar imaging and geophysics. Dr Idier has been involved in joint research programs with several specialized research centers: EDF (Electricite de France), CEA (Commissariat a l'Energie Atomique), CNES (Centre National d'Etudes Spatiales), ONERA (Office National d'Etudes et de Recherches Aerospatiales), Loreal, Thales, Schlumberger.
"About the title" may belong to another edition of this title.
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