An Introduction to Data Analysis and Uncertainty Quantification for Inverse Problems

An Introduction to Data Analysis and Uncertainty Quantification for Inverse Problems
Author :
Publisher : SIAM
Total Pages : 275
Release :
ISBN-10 : 9781611974911
ISBN-13 : 1611974917
Rating : 4/5 (917 Downloads)

Book Synopsis An Introduction to Data Analysis and Uncertainty Quantification for Inverse Problems by : Luis Tenorio

Download or read book An Introduction to Data Analysis and Uncertainty Quantification for Inverse Problems written by Luis Tenorio and published by SIAM. This book was released on 2017-07-06 with total page 275 pages. Available in PDF, EPUB and Kindle. Book excerpt: Inverse problems are found in many applications, such as medical imaging, engineering, astronomy, and geophysics, among others. To solve an inverse problem is to recover an object from noisy, usually indirect observations. Solutions to inverse problems are subject to many potential sources of error introduced by approximate mathematical models, regularization methods, numerical approximations for efficient computations, noisy data, and limitations in the number of observations; thus it is important to include an assessment of the uncertainties as part of the solution. Such assessment is interdisciplinary by nature, as it requires, in addition to knowledge of the particular application, methods from applied mathematics, probability, and statistics. This book bridges applied mathematics and statistics by providing a basic introduction to probability and statistics for uncertainty quantification in the context of inverse problems, as well as an introduction to statistical regularization of inverse problems. The author covers basic statistical inference, introduces the framework of ill-posed inverse problems, and explains statistical questions that arise in their applications. An Introduction to Data Analysis and Uncertainty Quantification for Inverse Problems?includes many examples that explain techniques which are useful to address general problems arising in uncertainty quantification, Bayesian and non-Bayesian statistical methods and discussions of their complementary roles, and analysis of a real data set to illustrate the methodology covered throughout the book.


An Introduction to Data Analysis and Uncertainty Quantification for Inverse Problems Related Books

An Introduction to Data Analysis and Uncertainty Quantification for Inverse Problems
Language: en
Pages: 275
Authors: Luis Tenorio
Categories: Mathematics
Type: BOOK - Published: 2017-07-06 - Publisher: SIAM

GET EBOOK

Inverse problems are found in many applications, such as medical imaging, engineering, astronomy, and geophysics, among others. To solve an inverse problem is t
An Introduction to Data Analysis and Uncertainty Quantification for Inverse Problems
Language: en
Pages: 269
Authors: Luis Tenorio
Categories: Electronic books
Type: BOOK - Published: 2017 - Publisher:

GET EBOOK

Abstract: Inverse problems are found in many applications, such as medical imaging, engineering, astronomy, and geophysics, among others. To solve an inverse pr
Computational Uncertainty Quantification for Inverse Problems
Language: en
Pages: 141
Authors: Johnathan M. Bardsley
Categories: Science
Type: BOOK - Published: 2018-08-01 - Publisher: SIAM

GET EBOOK

This book is an introduction to both computational inverse problems and uncertainty quantification (UQ) for inverse problems. The book also presents more advanc
Large-Scale Inverse Problems and Quantification of Uncertainty
Language: en
Pages: 403
Authors: Lorenz Biegler
Categories: Mathematics
Type: BOOK - Published: 2011-06-24 - Publisher: John Wiley & Sons

GET EBOOK

This book focuses on computational methods for large-scale statistical inverse problems and provides an introduction to statistical Bayesian and frequentist met
Introduction to Inverse Problems in Imaging
Language: en
Pages: 358
Authors: M. Bertero
Categories: Science
Type: BOOK - Published: 2021-12-20 - Publisher: CRC Press

GET EBOOK

Fully updated throughout and with several new chapters, this second edition of Introduction to Inverse Problems in Imaging guides advanced undergraduate and gra