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Modeling and Inverse Problems in the Presence of Uncertainty

Modeling and Inverse Problems in the Presence of Uncertainty collects recent research-including the authors' own substantial projects-on;

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Modeling and Inverse Problems in the Presence of Uncertainty

Modeling and Inverse Problems in the Presence of Uncertainty collects recent research-including the authors' own substantial projects-on;

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Residual Stress, Thermomechanics & Infrared Imaging and Inverse Problems, Volume 6

Residual Stress, Thermomechanics & Infrared Imaging and Inverse Problems, Volume 6 of the Proceedings of the 2019 SEM Annual Conference;

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An Introduction to Data Analysis and Uncertainty Quantification for Inverse Problems

data, and limitations in the number of observations; thus it is important to include an assessment of the uncertainties as part of the solution;

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Inverse Problems

. The computational methods include nonsmooth optimization algorithms, direct inversion methods and uncertainty quantification via Bayesian;

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Advanced Mechatronics

overview of the main results in the inverse problem theory and continues with the presentation of basic results in discrete inverse theory. The;

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Large-Scale Inverse Problems and Quantification of Uncertainty

methods for simulation of the forward problem, such as, fast Partial Differential Equation (PDE) solvers, reduced-order models and emulators;

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Inverse Problems And Applications

Inverse problems lie at the heart of contemporary scientific inquiry and technological development. Applications include a variety;

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Computational Methods for Inverse Problems in Imaging

aspects and applications. The formulation of inverse problems in imaging requires accurate mathematical modeling in order to preserve the;

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Computational Methods for Inverse Problems in Imaging

aspects and applications. The formulation of inverse problems in imaging requires accurate mathematical modeling in order to preserve the;

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Thermal Measurements and Inverse Techniques

increase understanding of interactions between technological systems and nature, by bridging the gap between data derived from measurements and;

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Thermal Measurements and Inverse Techniques

increase understanding of interactions between technological systems and nature, by bridging the gap between data derived from measurements and;

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The Double Constraint Inversion Methodology

, and flood prediction. This approach takes into consideration the physics - for instance, the boundary conditions required to obtain a well;

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Model Validation and Uncertainty Quantification, Volume 3

Model Validation and Uncertainty Quantification, Volume 3: Proceedings of the 37th IMAC, A Conference and Exposition on Structural Dynamics;

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High-order Adjoint Sensitivity Analysis Methodology for Large-scale Nonlinear Systems

published by CRC Press. This breakthrough has many applications in sensitivity and uncertainty analysis, optimization, data assimilation, model;

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Modeling Uncertainty In Earth Sciences

Modeling Uncertainty in the Earth Sciences highlights the various issues, techniques and practical modeling tools available for modeling;

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Mathematical Methods in Image Processing and Inverse Problems

methods and techniques were discussed. The state-of-the-art developments on mathematical analysis, advanced modeling, efficient algorithm and;

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Approximate Dynamic Programming

problems that involve making decisions in the presence of uncertainty. With a focus on modeling and algorithms in conjunction with the language;

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Inverse Problems in the Mathematical Sciences

Inverse problems are immensely important in modern science and technology. However, the broad mathematical issues raised by inverse;

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Uncertainty Modeling and Analysis in Engineering and the Sciences

of uncertainty and a reliance on expert opinions. Uncertainty Modeling and Analysis in Engineering and the Sciences prepares current and future analysts;

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Applications of the Topological Derivative Method

The book presents new results and applications of the topological derivative method in control theory, topology optimization and inverse;

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A Novel Framework for the Modeling of Cardiac Electrophysiology

regions that characterize the cardiac electrical activity. This allows the model to solve the forward and inverse electrocardiology problems;

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Regularization Algorithms for Ill-Posed Problems

operator equations, both linear and nonlinear. These approximation schemes form a basis for implementable numerical algorithms for the stable;

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A Functional Analysis Framework for Modeling, Estimation and Control in Science and Engineering

teaching from the past 20 years, the author explains how functional analysis can be the basis of modern partial differential equation (PDE) and;

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A Functional Analysis Framework for Modeling, Estimation and Control in Science and Engineering

teaching from the past 20 years, the author explains how functional analysis can be the basis of modern partial differential equation (PDE) and;

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Inverse Problems in Engineering Mechanics III

concerned with the determination of the input and the characteristics of a system, given certain aspects of its output. Mathematically, such;

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Uncertainty Modeling and Analysis in Civil Engineering

) in their decisions at all levels. Uncertainty Modeling and Analysis in Civil Engineering provides a thorough report on the immediate state;

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