An Introduction to Data Analysis and Uncertainty Quantification for Inverse Problems, Luis Tenorio

Автор: Olivier Le Maitre; Omar M Knio
Название: Spectral Methods for Uncertainty Quantification
ISBN: 9400731922 ISBN-13(EAN): 9789400731929
Издательство: Springer
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Цена: 79190.00 T
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Описание: This book presents applications of spectral methods to problems of uncertainty propagation and quantification in model-based computations, focusing on the computational and algorithmic features of these methods most useful in dealing with models based on partial differential equations, in particular models arising in simulations of fluid flows.

Автор: Sullivan, T.J.
Название: Introduction to Uncertainty Quantification
ISBN: 3319233947 ISBN-13(EAN): 9783319233949
Издательство: Springer
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Цена: 55890.00 T
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Описание: This text provides a framework in which the main objectives of the field of uncertainty quantification (UQ) are defined and an overview of the range of mathematical methods by which they can be achieved. Complete with exercises throughout, the book will equip readers with both theoretical understanding and practical experience of the key mathematical and algorithmic tools underlying the treatment of uncertainty in modern applied mathematics. Students and readers alike are encouraged to apply the mathematical methods discussed in this book to their own favorite problems to understand their strengths and weaknesses, also making the text suitable for a self-study. Uncertainty quantification is a topic of increasing practical importance at the intersection of applied mathematics, statistics, computation and numerous application areas in science and engineering. This text is designed as an introduction to UQ for senior undergraduate and graduate students with a mathematical or statistical background and also for researchers from the mathematical sciences or from applications areas who are interested in the field.

Автор: Biegler
Название: Large-Scale Inverse Problems and Quantification of Uncertainty
ISBN: 0470697431 ISBN-13(EAN): 9780470697436
Издательство: Wiley
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Цена: 118220.00 T
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Описание: 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.

Автор: Johnathan M. Bardsley
Название: Computational Uncertainty Quantification for Inverse Problems
ISBN: 1611975379 ISBN-13(EAN): 9781611975376
Издательство: Mare Nostrum (Eurospan)
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Цена: 53090.00 T
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Описание: This book is an introduction to both computational inverse problems and uncertainty quantification (UQ) for inverse problems. The book also presents more advanced material on Bayesian methods and UQ, including Markov chain Monte Carlo sampling methods for UQ in inverse problems. Each chapter contains MATLAB® code that implements the algorithms and generates the figures, as well as a large number of exercises accessible to both graduate students and researchers. Computational Uncertainty Quantification for Inverse Problems is intended for graduate students, researchers, and applied scientists. It is appropriate for courses on computational inverse problems, Bayesian methods for inverse problems, and UQ methods for inverse problems.

Автор: Jadamba
Название: Uncertainty Quantification In Varia
ISBN: 1138626325 ISBN-13(EAN): 9781138626324
Издательство: Taylor&Francis
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Цена: 112290.00 T
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Описание: The primary objective of this book is to present a comprehensive treatment of uncertainty quantification in variational inequalities and some of its generalizations emerging from various network, economic, and engineering models. Some of the developed techniques also apply to machine learning, neural networks, and related fields.

Автор: Hester Bijl; Didier Lucor; Siddhartha Mishra; Chri
Название: Uncertainty Quantification in Computational Fluid Dynamics
ISBN: 3319346660 ISBN-13(EAN): 9783319346663
Издательство: Springer
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Цена: 102480.00 T
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Описание: It collects seven original review articles that cover improved versions of the Monte Carlo method (the so-called multi-level Monte Carlo method (MLMC)), moment-based stochastic Galerkin methods and modified versions of the stochastic collocation methods that use adaptive stencil selection of the ENO-WENO type in both physical and stochastic space.

Автор: Luis Chase
Название: Uncertainty Quantification: Advances in Research and Applications
ISBN: 1536148628 ISBN-13(EAN): 9781536148626
Издательство: Nova Science
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Цена: 77080.00 T
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Описание: In recent times, polynomial chaos expansion has emerged as a dominant technique to determine the response uncertainties of a system by propagating the uncertainties of the inputs. In this regard, the opening chapter of Uncertainty Quantification: Advances in Research and Applications, an intrusive approach called Galerkin Projection as well as non-intrusive approaches (such as pseudo-spectral projection and linear regression) are discussed.Next, the authors introduce a new methodology to determine the uncertainties of input parameters using CIRCE software to overcome the reliance on expert judgment. The goal is to determinate and evaluate the uncertainty bounds for physical models related to reflood model of MARS-KS code Vessel module (coupled with COBRA-TF) using both CIRCE and the experimental data of FEBA.Lastly, uncertainties related to rheological model parameters of skeletal muscles are modeled and analyzed, and available data are acquired and fused for hyperelastic constitutive model parameters with Neo-Hookean and Mooney-Rivlin formulations.

Автор: Charles L. Webber, Jr.; Norbert Marwan
Название: Recurrence Quantification Analysis
ISBN: 3319071548 ISBN-13(EAN): 9783319071541
Издательство: Springer
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Цена: 88500.00 T
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Описание: The analysis of recurrences in dynamical systems by using recurrence plots and their quantification is still an emerging field.

Автор: Bertero, Mario Boccaci, Patrizia Boccacci, P.
Название: Introduction to inverse problems in imaging
ISBN: 0750304359 ISBN-13(EAN): 9780750304351
Издательство: Taylor&Francis
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Цена: 70430.00 T
Наличие на складе: Нет в наличии.
Описание: A textbook on the principles of linear inverse problems, methods of their approximate solution, and practical application in imaging. It presents easily implementable and fast solution algorithms. It provides the reader with the background for an understanding of the essence of inverse problems (ill-posedness and its cure).

Автор: Geba Dan-Andrei, Grillakis Manoussos G.
Название: An Introduction to the Theory of Wave Maps and Related Geometric Problems
ISBN: 9814713902 ISBN-13(EAN): 9789814713900
Издательство: World Scientific Publishing
Цена: 68640.00 T
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Описание: The wave maps system is one of the most beautiful and challenging nonlinear hyperbolic systems, which has captured the attention of mathematicians for more than thirty years now.

Автор: Martin Stynes, David Stynes
Название: Convection-Diffusion Problems: An Introduction to Their Analysis and Numerical Solution
ISBN: 1470448688 ISBN-13(EAN): 9781470448684
Издательство: Mare Nostrum (Eurospan)
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Цена: 112860.00 T
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Описание: Many physical problems involve diffusive and convective (transport) processes. When diffusion dominates convection, standard numerical methods work satisfactorily. But when convection dominates diffusion, the standard methods become unstable, and special techniques are needed to compute accurate numerical approximations of the unknown solution. This convection-dominated regime is the focus of the book. After discussing at length the nature of solutions to convection-dominated convection-diffusion problems, the authors motivate and design numerical methods that are particularly suited to this class of problems. At first they examine finite-difference methods for two-point boundary value problems, as their analysis requires little theoretical background. Upwinding, artificial diffusion, uniformly convergent methods, and Shishkin meshes are some of the topics presented. Throughout, the authors are concerned with the accuracy of solutions when the diffusion coefficient is close to zero. Later in the book they concentrate on finite element methods for problems posed in one and two dimensions.This lucid yet thorough account of convection-dominated convection-diffusion problems and how to solve them numerically is meant for beginning graduate students, and it includes a large number of exercises. An up-to-date bibliography provides the reader with further reading. This book is published in cooperation with Atlantic Association for Research in the Mathematical Sciences.

Автор: Shi Jin; Lorenzo Pareschi
Название: Uncertainty Quantification for Hyperbolic and Kinetic Equations
ISBN: 331967109X ISBN-13(EAN): 9783319671093
Издательство: Springer
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Цена: 88500.00 T
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Описание: This book explores recent advances in uncertainty quantification for hyperbolic, kinetic, and related problems. The contributions address a range of different aspects, including: polynomial chaos expansions, perturbation methods, multi-level Monte Carlo methods, importance sampling, and moment methods.