Titlebook: Optimization and Regularization for Computational Inverse Problems and Applications; Yanfei Wang,Changchun Yang,Anatoly G. Yagola Book 201

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Some Reconstruction Methods for Inverse Scattering Problemsinite dimensional space, some regularizing term should be introduced to the cost functional..Although these general optimization techniques have been applied widely in the last century, they also suffer from many disadvantages theoretically and numerically. From the theoretical point of view, the la

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Inverse Problems of Molecular Spectra Data Processing have constructed a principle for choosing a unique solution from the set of solutions in the framework of Tikhonov’s regularization theory. The solution is chosen as the nearest to the given matrix of force constants which satisfy all . assumptions concerning the model characteristics of the soluti

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Numerical Inversion Methods in Geoscience and Quantitative Remote Sensinghese issues exist for all quantitative remote sensing inverse problems. For example, when sampling is poor, i.e., there are very few observations, or directions are poorly located, the inversion process would be underdetermined, which leads to the large condition number of the normalized systems and

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Pseudo-Differential Operator and Inverse Scattering of Multidimensional Wave Equatione scattering problem, namely, effective one-way operator integral representation, differential form of wave equation in ray coordinate, wide application of Witt product and the modern development of multidimensional spectral factorization. The example of spectrum factorization shows that the energy

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Book 2011 students engaged in applied mathematics, engineering, geophysics, medical science, image processing, remote sensing and atmospheric science will benefit from this book.Dr. Yanfei Wang is a Professor at the Institute of Geology and Geophysics, Chinese Academy of Sciences, China.Dr. Sc. Anatoly G. Ya

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processing, remote sensing and atmospheric science will benefit from this book.Dr. Yanfei Wang is a Professor at the Institute of Geology and Geophysics, Chinese Academy of Sciences, China.Dr. Sc. Anatoly G. Ya978-3-642-13742-6

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Ill-Posed Problems and Methods for Their Numerical Solutionn are described. Hadamard’s definition of well-posedness and examples of ill-posed problems are given. Tikhonov’s definition of a regularizing algorithm and classification of mathematical problems are described. The main properties of ill-posed problems are discussed. As an example of . information

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Regularization of Naturally Linearized Parameter Identification Problems and the Application of the linearization of an identification problem with the Tikhonov scheme, where the regularization parameter is chosen adaptively by means of the so-called balancing principle. We describe the natural linearization approach and show how it can be treated within the framework of Tikhonov regularization a