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Titlebook: Numerical Regularization for Atmospheric Inverse Problems; Adrian Doicu,Thomas Trautmann,Franz Schreier Book 2010 Springer-Verlag Berlin H

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書目名稱Numerical Regularization for Atmospheric Inverse Problems
編輯Adrian Doicu,Thomas Trautmann,Franz Schreier
視頻videohttp://file.papertrans.cn/670/669166/669166.mp4
概述Presents regularization methods for atmospheric retrieval, based on the authors work.Focuses on computational aspects but also provides some theoretical results.Surveys the state-of-the-art numerical
叢書名稱Springer Praxis Books
圖書封面Titlebook: Numerical Regularization for Atmospheric Inverse Problems;  Adrian Doicu,Thomas Trautmann,Franz Schreier Book 2010 Springer-Verlag Berlin H
描述The retrieval problems arising in atmospheric remote sensing belong to the class of the - called discrete ill-posed problems. These problems are unstable under data perturbations, and can be solved by numerical regularization methods, in which the solution is stabilized by taking additional information into account. The goal of this research monograph is to present and analyze numerical algorithms for atmospheric retrieval. The book is aimed at physicists and engineers with some ba- ground in numerical linear algebra and matrix computations. Although there are many practical details in this book, for a robust and ef?cient implementation of all numerical algorithms, the reader should consult the literature cited. The data model adopted in our analysis is semi-stochastic. From a practical point of view, there are no signi?cant differences between a semi-stochastic and a determin- tic framework; the differences are relevant from a theoretical point of view, e.g., in the convergence and convergence rates analysis. After an introductory chapter providing the state of the art in passive atmospheric remote sensing, Chapter 2 introduces the concept of ill-posedness for linear discrete eq-
出版日期Book 2010
關鍵詞Inversion; Mathematica; algorithms; atmospheric science; boundary element method; development; entropy; mat
版次1
doihttps://doi.org/10.1007/978-3-642-05439-6
isbn_softcover978-3-642-42401-4
isbn_ebook978-3-642-05439-6
copyrightSpringer-Verlag Berlin Heidelberg 2010
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Iterative regularization methods for nonlinear problems,
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Numerical Regularization for Atmospheric Inverse Problems
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theoretical results.Surveys the state-of-the-art numerical The retrieval problems arising in atmospheric remote sensing belong to the class of the - called discrete ill-posed problems. These problems are unstable under data perturbations, and can be solved by numerical regularization methods, in wh
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978-3-642-42401-4Springer-Verlag Berlin Heidelberg 2010
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