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Optimal Methods for Ill-Posed Problems

The book covers fundamentals of the theory of optimal methods for solving ill-posed problems, as well as ways to obtain accurate and;

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Regularization Methods for Ill-Posed Optimal Control Problems

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Numerical Methods of Solving Ill-Posed Problems of Dielectric Spectrometry

Numerical Methods of Solving Ill-Posed Problems of Dielectric Spectrometry;

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Regularization Algorithms for Ill-Posed Problems

physics. The book presents in detail stable solution methods for ill-posed problems using the methodology of iterative regularization of classical;

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Dynamical Systems Method and Applications

, well-posed or ill-posed. The book presents a systematic development of the DSM, and theoretical results are illustrated by a number;

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Abstract Cauchy Problems

Although the theory of well-posed Cauchy problems is reasonably understood, ill-posed problems-involved in a numerous mathematical models;

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Abstract Cauchy Problems

Although the theory of well-posed Cauchy problems is reasonably understood, ill-posed problems-involved in a numerous mathematical models;

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Rank-Deficient and Discrete Ill-Posed Problems

for the analysis and solution of rank-deficient and discrete ill-posed problems. The emphasis is on insight into the stabilizing properties;

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Inverse and Ill-posed Problems

information about its solution. Inverse problems were first encountered in practice and are mostly ill-posed. The urgent need for their solution;

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Inverse Problems and Applications

analytical developments and numerical methods for solutions of inverse and ill-posed problems, which consistently pose complex challenges to the;

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Ill-Posed Problems in Probability & Stability of Random Sums

This volume is concerned with the problems in probability and statistics. Ill-posed problems are usually understood as those results where;

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Conjugate Gradient Type Methods for Ill-Posed Problems

) to ill posed problems and their regularization. Such problems occur in applications from almost all natural and technical sciences, including;

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Conjugate Gradient Type Methods for Ill-Posed Problems

) to ill posed problems and their regularization. Such problems occur in applications from almost all natural and technical sciences, including;

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Inverse Problems in Physical Diagnostics

procedure for physicists, but, because there is no proportionality between data and solution errors in ill-posed problems, such approach;

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Spline Models for Observational Data

the very important area of (Tikhonov) regularization methods for ill posed inverse problems. Convergence properties, data based smoothing;

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An Introduction to the Mathematical Theory of Inverse Problems

ill-posed problems, analyzing basic properties of regularization methods for ill-posed problems via several simple analytical and numerical;

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An Introduction to the Mathematical Theory of Inverse Problems

ill-posed problems, analyzing basic properties of regularization methods for ill-posed problems via several simple analytical and numerical;

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Inverse Stefan Problems

boundaries. This new approach to the theory of ill-posed problems is useful for the modelling of nonlinear processes with phase transforms;

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Advanced Mechatronics

control of distributed systems is presented in the general framework of the recently developed ill-posed inverse problems. The book starts with an;

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Dynamical Systems Method for Solving Nonlinear Operator Equations

analysis, and ill-posed and inverse problems especially. The book presents a general method for solving operator equations, especially nonlinear;

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New Trends in Parameter Identification for Mathematical Models

regularization methods in Hilbert and Banach spaces for the stable approximate solution of ill-posed inverse problems, novel methods for parameter;

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Symplectic Pseudospectral Methods for Optimal Control

The book focuses on symplectic pseudospectral methods for nonlinear optimal control problems and their applications. Both the fundamental;

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Advances in Computational Mathematics

, computational approximation, numerical solutions of differential and integral equations, numerical linear algebra, inverse and ill-posed problems;

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Maximum Entropy Econometrics

new basis for learning from economic and statistical models that may be non-regular in the sense that they are ill-posed or underdetermined;

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An Information Theoretic Approach to Econometrics

models and methods. Because most data are observational, practitioners work with indirect noisy observations and ill-posed econometric models;

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An Information Theoretic Approach to Econometrics

models and methods. Because most data are observational, practitioners work with indirect noisy observations and ill-posed econometric models;

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Mathematical and Numerical Approaches for Multi-Wave Inverse Problems

, and geophysics, to name but a few. In turn, it is well known that inverse problems are both nonlinear and ill-posed: two factors that pose;

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