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Inverse problem theory and methods for model parameter estimation / Albert Tarantola
Mitwirkende(r): Resource type: Ressourcentyp: Buch (Online)Buch (Online)Sprache: Englisch Reihen: Other titles in applied mathematics ; 89Verlag: Philadelphia, Pa. : Society for Industrial and Applied Mathematics, 2005Beschreibung: Online-Ressource (1 electronic text xii, 342 p.)ISBN:- 0898715725
- 9780898715729
- 9780898717921
- 9780898717921
- 515/.357
- QA371
Inhalte:
Zusammenfassung: While the prediction of observations is a forward problem, the use of actual observations to infer the properties of a model is an inverse problem. Inverse problems are difficult because they may not have a unique solution. The description of uncertainties plays a central role in the theory, which is based on probability theory. This book proposes a general approach that is valid for linear as well as for nonlinear problems. The philosophy is essentially probabilistic and allows the reader to understand the basic difficulties appearing in the resolution of inverse problems. The book attempts to explain how a method of acquisition of information can be applied to actual real-world problems, and many of the arguments are heuristicPPN: PPN: 640156142Package identifier: Produktsigel: ZDB-72-SIA
Includes bibliographical references (p. 317-332) and index
Chapter 1: The General Discrete Inverse Problem -- Chapter 2: Monte Carlo Methods -- Chapter 3: The Least-Squares Criterion -- Chapter 4: Least-Absolute Values Criterion and Minimax Criterion -- Chapter 5: Functional Inverse Problems -- Chapter 6: Appendices -- Chapter 7: Problems -- References -- Index.
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