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Inverse Problems Basics, Theory and Applications in Geophysics /

The overall goal of the book is to provide access to the regularized solution of inverse problems relevant in geophysics without requiring more mathematical knowledge than is taught in undergraduate math courses for scientists and engineers. From abstract analysis only the concept of functions as ve...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Richter, Mathias (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Cham : Springer International Publishing : Imprint: Birkhäuser, 2016.
Edición:1st ed. 2016.
Colección:Lecture Notes in Geosystems Mathematics and Computing,
Temas:
Acceso en línea:Texto Completo

MARC

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490 1 |a Lecture Notes in Geosystems Mathematics and Computing,  |x 2512-3211 
505 0 |a 1.Characterization of Inverse Problems -- 2.Discretization of Inverse Problems -- 3.Regularization of Linear Inverse Problems -- 4.Regularization of Nonlinear Inverse Problems -- Appendix: A.Results from Linear Algebra -- B.Function Spaces -- C.The Fourier Transform -- D.Proofs of Theorems from Chapter 3. 
520 |a The overall goal of the book is to provide access to the regularized solution of inverse problems relevant in geophysics without requiring more mathematical knowledge than is taught in undergraduate math courses for scientists and engineers. From abstract analysis only the concept of functions as vectors is needed. Function spaces are introduced informally in the course of the text, when needed. Additionally, a more detailed, but still condensed introduction is given in Appendix B. A second goal is to elaborate the single steps to be taken when solving an inverse problem: discretization, regularization and practical solution of the regularized optimization problem. These steps are shown in detail for model problems from the fields of inverse gravimetry and seismic tomography. The intended audience is mathematicians, physicists and engineers having a good working knowledge of linear algebra and analysis at the upper undergraduate level. 
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