Rank-Deficient and Discrete Ill-Posed Problems

Rank-Deficient and Discrete Ill-Posed Problems PDF

Author: Per Christian Hansen

Publisher: SIAM

Published: 2005-01-01

Total Pages: 259

ISBN-13: 0898714036

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Here is an overview of modern computational stabilization methods for linear inversion, with applications to a variety of problems in audio processing, medical imaging, tomography, seismology, astronomy, and other areas. Rank-deficient problems involve matrices that are either exactly or nearly rank deficient. Such problems often arise in connection with noise suppression and other problems where the goal is to suppress unwanted disturbances of the given measurements. Discrete ill-posed problems arise in connection with the numerical treatment of inverse problems, where one typically wants to compute information about some interior properties using exterior measurements. Examples of inverse problems are image restoration and tomography, where one needs to improve blurred images or reconstruct pictures from raw data. This book describes, in a common framework, new and existing numerical methods for the analysis and solution of rank-deficient and discrete ill-posed problems. The emphasis is on insight into the stabilizing properties of the algorithms and on the efficiency and reliability of the computations. The setting is that of numerical linear algebra rather than abstract functional analysis, and the theoretical development is complemented with numerical examples and figures that illustrate the features of the various algorithms.

A Taste of Inverse Problems

A Taste of Inverse Problems PDF

Author: Martin Hanke

Publisher: SIAM

Published: 2017-01-01

Total Pages: 171

ISBN-13: 1611974933

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Inverse problems need to be solved in order to properly interpret indirect measurements. Often, inverse problems are ill-posed and sensitive to data errors. Therefore one has to incorporate some sort of regularization to reconstruct significant information from the given data. A Taste of Inverse Problems: Basic Theory and Examples?presents the main achievements that have emerged in regularization theory over the past 50 years, focusing on linear ill-posed problems and the development of methods that can be applied to them. Some of this material has previously appeared only in journal articles. This book rigorously discusses state-of-the-art inverse problems theory, focusing on numerically relevant aspects and omitting subordinate generalizations; presents diverse real-world applications, important test cases, and possible pitfalls; and treats these applications with the same rigor and depth as the theory.

Handbook of Mathematical Methods in Imaging

Handbook of Mathematical Methods in Imaging PDF

Author: Otmar Scherzer

Publisher: Springer Science & Business Media

Published: 2010-11-23

Total Pages: 1626

ISBN-13: 0387929193

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The Handbook of Mathematical Methods in Imaging provides a comprehensive treatment of the mathematical techniques used in imaging science. The material is grouped into two central themes, namely, Inverse Problems (Algorithmic Reconstruction) and Signal and Image Processing. Each section within the themes covers applications (modeling), mathematics, numerical methods (using a case example) and open questions. Written by experts in the area, the presentation is mathematically rigorous. The entries are cross-referenced for easy navigation through connected topics. Available in both print and electronic forms, the handbook is enhanced by more than 150 illustrations and an extended bibliography. It will benefit students, scientists and researchers in applied mathematics. Engineers and computer scientists working in imaging will also find this handbook useful.

Parameter Estimation and Inverse Problems

Parameter Estimation and Inverse Problems PDF

Author: Richard C. Aster

Publisher: Elsevier

Published: 2018-10-16

Total Pages: 404

ISBN-13: 0128134232

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Parameter Estimation and Inverse Problems, Third Edition, is structured around a course at New Mexico Tech and is designed to be accessible to typical graduate students in the physical sciences who do not have an extensive mathematical background. The book is complemented by a companion website that includes MATLAB codes that correspond to examples that are illustrated with simple, easy to follow problems that illuminate the details of particular numerical methods. Updates to the new edition include more discussions of Laplacian smoothing, an expansion of basis function exercises, the addition of stochastic descent, an improved presentation of Fourier methods and exercises, and more. Features examples that are illustrated with simple, easy to follow problems that illuminate the details of a particular numerical method Includes an online instructor’s guide that helps professors teach and customize exercises and select homework problems Covers updated information on adjoint methods that are presented in an accessible manner

Lunar Gravimetry

Lunar Gravimetry PDF

Author: Rune Floberghagen

Publisher: Springer Science & Business Media

Published: 2012-08-27

Total Pages: 296

ISBN-13: 9048195527

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Lunar Gravimetry: Revealing the Far-Side provides a thorough and detailed discussion of lunar gravity field research and applications, from the initial efforts of the pre-Apollo and Luna eras to the dedicated gravity mapping experiments of the third millennium. Analysis of the spatial variations of the gravity field of the Moon is a key selenodetic element in the understanding of the physics of the Moon's interior. Remarkably, more than forty years after the initial steps in lunar exploration by spacecraft, the global gravity field still remains largely unknown, due to the limitations of standard observations techniques. As such, knowledge of the high-accuracy and high-resolution gravity field is one of the remaining unsolved issues in lunar science.

Numerical Methods for Least Squares Problems

Numerical Methods for Least Squares Problems PDF

Author: Ake Bjorck

Publisher: SIAM

Published: 1996-01-01

Total Pages: 425

ISBN-13: 9781611971484

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The method of least squares was discovered by Gauss in 1795. It has since become the principal tool to reduce the influence of errors when fitting models to given observations. Today, applications of least squares arise in a great number of scientific areas, such as statistics, geodetics, signal processing, and control. In the last 20 years there has been a great increase in the capacity for automatic data capturing and computing. Least squares problems of large size are now routinely solved. Tremendous progress has been made in numerical methods for least squares problems, in particular for generalized and modified least squares problems and direct and iterative methods for sparse problems. Until now there has not been a monograph that covers the full spectrum of relevant problems and methods in least squares. This volume gives an in-depth treatment of topics such as methods for sparse least squares problems, iterative methods, modified least squares, weighted problems, and constrained and regularized problems. The more than 800 references provide a comprehensive survey of the available literature on the subject.

Facts, Conjectures, and Improvements for Simulated Annealing

Facts, Conjectures, and Improvements for Simulated Annealing PDF

Author: Peter Salamon

Publisher: SIAM

Published: 2002-01-01

Total Pages: 163

ISBN-13: 9780898718300

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An introduction to simulated annealing. This book brings together for the first time many of the theoretical foundations for improvements to algorithms for global optimization that until now existed only in scattered research articles.

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