Regularization Algorithms for Ill-Posed Problems, Bakushinsky Anatoly B., Kokurin Mikhail M., Kokurin Mikhail Yu
Автор: S.F. Gilyazov; N.L. Gol`dman Название: Regularization of Ill-Posed Problems by Iteration Methods ISBN: 9048153824 ISBN-13(EAN): 9789048153824 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Iteration regularization, i.e., utilization of iteration methods of any form for the stable approximate solution of ill-posed problems, is one of the most important but still insufficiently developed topics of the new theory of ill-posed problems.
Автор: Michel Thera; Rainer Tichatschke Название: Ill-posed Variational Problems and Regularization Techniques ISBN: 3540663231 ISBN-13(EAN): 9783540663232 Издательство: Springer Рейтинг: Цена: 15372.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Developments in the field of ill-posed variational problems and variational inequalities are presented here. The work covers a large range of theoretical, numerical and practical aspects.
Автор: S.F. Gilyazov; N.L. Gol`dman Название: Regularization of Ill-Posed Problems by Iteration Methods ISBN: 0792361318 ISBN-13(EAN): 9780792361312 Издательство: Springer Рейтинг: Цена: 15372.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Iteration regularization, i.e., utilization of iteration methods of any form for the stable approximate solution of ill-posed problems, is one of the most important but still insufficiently developed topics of the new theory of ill-posed problems.
Автор: Mongi A. Abidi; Andrei V. Gribok; Joonki Paik Название: Optimization Techniques in Computer Vision ISBN: 3319463632 ISBN-13(EAN): 9783319463636 Издательство: Springer Рейтинг: Цена: 18167.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book presents practical optimization techniques used in image processing and computer vision problems. Ill-posed problems are introduced and used as examples to show how each type of problem is related to typical image processing and computer vision problems. Unconstrained optimization gives the best solution based on numerical minimization of a single, scalar-valued objective function or cost function. Unconstrained optimization problems have been intensively studied, and many algorithms and tools have been developed to solve them. Most practical optimization problems, however, arise with a set of constraints. Typical examples of constraints include: (i) pre-specified pixel intensity range, (ii) smoothness or correlation with neighboring information, (iii) existence on a certain contour of lines or curves, and (iv) given statistical or spectral characteristics of the solution. Regularized optimization is a special method used to solve a class of constrained optimization problems. The term regularization refers to the transformation of an objective function with constraints into a different objective function, automatically reflecting constraints in the unconstrained minimization process. Because of its simplicity and efficiency, regularized optimization has many application areas, such as image restoration, image reconstruction, optical flow estimation, etc.
Optimization plays a major role in a wide variety of theories for image processing and computer vision. Various optimization techniques are used at different levels for these problems, and this volume summarizes and explains these techniques as applied to image processing and computer vision.
Автор: Adrian Doicu; Thomas Trautmann; Franz Schreier Название: Numerical Regularization for Atmospheric Inverse Problems ISBN: 3642424015 ISBN-13(EAN): 9783642424014 Издательство: Springer Рейтинг: Цена: 26120.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Written by brilliant mathematicians, this research monograph presents and analyzes numerical algorithms for atmospheric retrieval, pulling together all the relevant material in a consistent, very powerful manner.
Автор: Heinz Werner Engl; Martin Hanke; A. Neubauer Название: Regularization of Inverse Problems ISBN: 0792341570 ISBN-13(EAN): 9780792341574 Издательство: Springer Рейтинг: Цена: 15372.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Offers an overview over some classes of inverse problems. This book deals with the mathematical theory of regularization methods and gives an account of the results about regularization methods both for linear and for nonlinear ill-posed problems. It considers both continuous and iterative regularization methods.
Описание: The book collects and contributes new results on the theory and practice of ill-posed inverse problems. The new methods are applied to a difficult inverse problem from laser optics.Sparsity promoting regularization is examined in detail from a Banach space point of view.
Автор: Richard Huber Название: Variational Regularization for Systems of Inverse Problems ISBN: 3658253894 ISBN-13(EAN): 9783658253899 Издательство: Springer Рейтинг: Цена: 7685.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Tikhonov regularization is a cornerstone technique in solving inverse problems with applications in countless scienti?c ?elds. Richard Huber discusses a multi-parameter Tikhonov approach for systems of inverse problems in order to take advantage of their speci?c structure. Such an approach allows to choose the regularization weights of each subproblem individually with respect to the corresponding noise levels and degrees of ill-posedness.
Описание: This book covers both the methods, including standard regularization theory, Fejer processes for linear and nonlinear problems, the balancing principle, extrapolated regularization, nonstandard regularization, nonlinear gradient method, the nonmonotone gradient method, subspace method and Lie group method;
Автор: Bruno Cordani Название: The Kepler Problem ISBN: 303489421X ISBN-13(EAN): 9783034894210 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Because of the correspondences existing among all levels of reality, truths pertaining to a lower level can be considered as symbols of truths at a higher level and can therefore be the "foundation" or support leading by analogy to a knowledge of the latter.
Автор: Javier Roa Название: Regularization in Orbital Mechanics: Theory and Practice ISBN: 3110558556 ISBN-13(EAN): 9783110558555 Издательство: Walter de Gruyter Цена: 21013.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Regularized equations of motion can improve numerical integration for the propagation of orbits, and simplify the treatment of mission design problems. This monograph discusses standard techniques and recent research in the area. While each scheme is derived analytically, its accuracy is investigated numerically. Algebraic and topological aspects of the formulations are studied, as well as their application to practical scenarios such as spacecraft relative motion and new low-thrust trajectories.
Автор: Russo Название: Stochastic Calculus via Regularizations ISBN: 303109445X ISBN-13(EAN): 9783031094453 Издательство: Springer Рейтинг: Цена: 22359.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The book constitutes an introduction to stochastic calculus, stochastic differential equations and related topics such as Malliavin calculus. On the other hand it focuses on the techniques of stochastic integration and calculus via regularization initiated by the authors. The definitions relies on a smoothing procedure of the integrator process, they generalize the usual It? and Stratonovich integrals for Brownian motion but the integrator could also not be a semimartingale and the integrand is allowed to be anticipating. The resulting calculus requires a simple formalism: nevertheless it entails pathwise techniques even though it takes into account randomness. It allows connecting different types of pathwise and non pathwise integrals such as Young, fractional, Skorohod integrals, enlargement of filtration and rough paths. The covariation, but also high order variations, play a fundamental role in the calculus via regularization, which can also be applied for irregular integrators. A large class of Gaussian processes, various generalizations of semimartingales such that Dirichlet and weak Dirichlet processes are revisited. Stochastic calculus via regularization has been successfully used in applications, for instance in robust finance and on modeling vortex filaments in turbulence. The book is addressed to PhD students and researchers in stochastic analysis and applications to various fields.
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