Nonlinear Least Squares for Inverse Problems: Theoretical Foundations and Step-by-Step Guide for Applications
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Background: Ecole Polytechnique (Paris, 1965),
Ecole Nationale Supérieure des Télécommunications (Paris,1968),
Paris-6 University (Ph. D., 1971).
Professor Chavent joined the Faculty of Paris 9-Dauphine in 1971. He is now an emeritus professor from this university. During the same span of time, he ran a research project at INRIA (Institut National de Recherche en Informatique et en Automatique), focused on industrial inverse problems (oil production and exploration, nuclear reactors, ground water management...).
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Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The domain of inverse problems has experienced a rapid expansion, driven by the increase in computing power and the progress in numerical modeling. When I started working on this domain years ago, I became somehow fr- tratedtoseethatmyfriendsworkingonmodelingwhereproducingexistence, uniqueness, and stability results for the solution of their equations, but that I was most of the time limited, because of the nonlinearity of the problem, to provethatmyleastsquaresobjectivefunctionwasdi erentiable.Butwith my experience growing, I became convinced that, after the inverse problem has been properly trimmed, the nal least squares problem, the one solved on the computer, should be Quadratically (Q)-wellposed,thatis,both we- posed and optimizable: optimizability ensures that a global minimizer of the least squares function can actually be found using e cient local optimization algorithms, and wellposedness that this minimizer is stable with respect to perturbation of the data. But the vast majority of inverse problems are nonlinear, and the clas- cal mathematical tools available for their analysis fail to bring answers to these crucial questions: for example, compactness will ensure existence, but provides no uniqueness results, and brings no information on the presence or absenceofparasiticlocalminimaorstationarypoints. 360 pp. Englisch. N° de réf. du vendeur 9789048127849
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Gebunden. Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Step-by-step guide to solving Nonlinear Inverse Problems with Least Square methodsContains a geometric theory to analyze Wellposedness and OptimizabilityDetailed analysis of practical issues when solving Nonlinear Least Square problems. N° de réf. du vendeur 5817504
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