Computational Methods For Applied Inverse Problems

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Author: Yanfei Wang
Publisher: Walter de Gruyter
ISBN: 3110259052
Size: 22.94 MB
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Computational Methods For Applied Inverse Problems by Yanfei Wang


Original Title: Computational Methods For Applied Inverse Problems

This monograph reports recent advances of inversion theory and recent developments with practical applications in frontiers of sciences, especially inverse design and novel computational methods for inverse problems. Readers who do research in applied mathematics, engineering, geophysics, biomedicine, image processing, remote sensing, and environmental science will benefit from the contents since the book incorporates a background of using statistical and non-statistical methods, e.g., regularization and optimization techniques for solving practical inverse problems.

Applied Inverse Problems

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Author: Larisa Beilina
Publisher: Springer Science & Business Media
ISBN: 1461478162
Size: 37.29 MB
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Applied Inverse Problems by Larisa Beilina


Original Title: Applied Inverse Problems

This proceedings volume is based on papers presented at the First Annual Workshop on Inverse Problems which was held in June 2011 at the Department of Mathematics, Chalmers University of Technology. The purpose of the workshop was to present new analytical developments and numerical methods for solutions of inverse problems. State-of-the-art and future challenges in solving inverse problems for a broad range of applications was also discussed. The contributions in this volume are reflective of these themes and will be beneficial to researchers in this area.

Statistical And Computational Inverse Problems

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Author: Jari Kaipio
Publisher: Springer Science & Business Media
ISBN: 0387271325
Size: 18.45 MB
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Statistical And Computational Inverse Problems by Jari Kaipio


Original Title: Statistical And Computational Inverse Problems

This book covers the statistical mechanics approach to computational solution of inverse problems, an innovative area of current research with very promising numerical results. The techniques are applied to a number of real world applications such as limited angle tomography, image deblurring, electical impedance tomography, and biomagnetic inverse problems. Contains detailed examples throughout and includes a chapter on case studies where such methods have been implemented in biomedical engineering.

Computational Methods In Geophysical Electromagnetics

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Author: Eldad Haber
Publisher: SIAM
ISBN: 1611973805
Size: 36.49 MB
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Computational Methods In Geophysical Electromagnetics by Eldad Haber


Original Title: Computational Methods In Geophysical Electromagnetics

This monograph provides a framework for students and practitioners who are working on the solution of electromagnetic imaging in geophysics. Bridging the gap between theory and practical applied material (for example, inverse and forward problems), it provides a simple explanation of finite volume discretization, basic concepts in solving inverse problems through optimization, a summary of applied electromagnetics methods, and MATLAB?÷code for efficient computation.

Numerical Methods For Solving Inverse Problems Of Mathematical Physics

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Author: A. A. Samarskii
Publisher: Walter de Gruyter
ISBN: 3110205793
Size: 60.36 MB
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Numerical Methods For Solving Inverse Problems Of Mathematical Physics by A. A. Samarskii


Original Title: Numerical Methods For Solving Inverse Problems Of Mathematical Physics

The main classes of inverse problems for equations of mathematical physics and their numerical solution methods are considered in this book which is intended for graduate students and experts in applied mathematics, computational mathematics, and mathematical modelling.

Discrete Inverse Problems

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Author: Per Christian Hansen
Publisher: SIAM
ISBN: 089871883X
Size: 54.76 MB
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Discrete Inverse Problems by Per Christian Hansen


Original Title: Discrete Inverse Problems

This book gives an introduction to the practical treatment of inverse problems by means of numerical methods, with a focus on basic mathematical and computational aspects. To solve inverse problems, we demonstrate that insight about them goes hand in hand with algorithms.

Linear And Nonlinear Inverse Problems With Practical Applications

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Author: Jennifer L. Mueller
Publisher: SIAM
ISBN: 9781611972344
Size: 22.62 MB
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Linear And Nonlinear Inverse Problems With Practical Applications by Jennifer L. Mueller


Original Title: Linear And Nonlinear Inverse Problems With Practical Applications

Inverse problems arise in practical applications whenever there is a need to interpret indirect measurements. This book explains how to identify ill-posed inverse problems arising in practice and gives a hands-on guide to designing computational solution methods for them, with related codes on an accompanying website. The guiding linear inversion examples are the problem of image deblurring, x-ray tomography, and backward parabolic problems, including heat transfer. A thorough treatment of electrical impedance tomography is used as the guiding nonlinear inversion example which combines the analytic-geometric research tradition and the regularization-based school of thought in a fruitful manner. This book is complete with exercises and project topics, making it ideal as a classroom textbook or self-study guide for graduate and advanced undergraduate students in mathematics, engineering or physics who wish to learn about computational inversion. It also acts as a useful guide for researchers who develop inversion techniques in high-tech industry.

Large Scale Inverse Problems And Quantification Of Uncertainty

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Author: Lorenz Biegler
Publisher: John Wiley & Sons
ISBN: 1119957583
Size: 13.25 MB
Format: PDF
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Large Scale Inverse Problems And Quantification Of Uncertainty by Lorenz Biegler


Original Title: Large Scale Inverse Problems And Quantification Of Uncertainty

This book focuses on computational methods for large-scale statistical inverse problems and provides an introduction to statistical Bayesian and frequentist methodologies. Recent research advances for approximation methods are discussed, along with Kalman filtering methods and optimization-based approaches to solving inverse problems. The aim is to cross-fertilize the perspectives of researchers in the areas of data assimilation, statistics, large-scale optimization, applied and computational mathematics, high performance computing, and cutting-edge applications. The solution to large-scale inverse problems critically depends on methods to reduce computational cost. Recent research approaches tackle this challenge in a variety of different ways. Many of the computational frameworks highlighted in this book build upon state-of-the-art methods for simulation of the forward problem, such as, fast Partial Differential Equation (PDE) solvers, reduced-order models and emulators of the forward problem, stochastic spectral approximations, and ensemble-based approximations, as well as exploiting the machinery for large-scale deterministic optimization through adjoint and other sensitivity analysis methods. Key Features: • Brings together the perspectives of researchers in areas of inverse problems and data assimilation. • Assesses the current state-of-the-art and identify needs and opportunities for future research. • Focuses on the computational methods used to analyze and simulate inverse problems. • Written by leading experts of inverse problems and uncertainty quantification. Graduate students and researchers working in statistics, mathematics and engineering will benefit from this book.

Nonlinear Inverse Problems In Imaging

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Author: Jin Keun Seo
Publisher: John Wiley & Sons
ISBN: 1118478150
Size: 65.13 MB
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Nonlinear Inverse Problems In Imaging by Jin Keun Seo


Original Title: Nonlinear Inverse Problems In Imaging

This book provides researchers and engineers in the imaging field with the skills they need to effectively deal with nonlinear inverse problems associated with different imaging modalities, including impedance imaging, optical tomography, elastography, and electrical source imaging. Focusing on numerically implementable methods, the book bridges the gap between theory and applications, helping readers tackle problems in applied mathematics and engineering. Complete, self-contained coverage includes basic concepts, models, computational methods, numerical simulations, examples, and case studies. Provides a step-by-step progressive treatment of topics for ease of understanding. Discusses the underlying physical phenomena as well as implementation details of image reconstruction algorithms as prerequisites for finding solutions to non linear inverse problems with practical significance and value. Includes end of chapter problems, case studies and examples with solutions throughout the book. Companion website will provide further examples and solutions, experimental data sets, open problems, teaching material such as PowerPoint slides and software including MATLAB m files. Essential reading for Graduate students and researchers in imaging science working across the areas of applied mathematics, biomedical engineering, and electrical engineering and specifically those involved in nonlinear imaging techniques, impedance imaging, optical tomography, elastography, and electrical source imaging

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