9789400730601 - nonlinear least squares for inverse problems: theoretical foundations and step-by-step guide for applications di chavent, guy (12 risultati)
Lingua: Inglese
Editore: Springer, 2012
Serie: Scientific Computation, Libro 8 di 36. Libro 8 di 36 - Scientific Computation
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Altre immaginiLingua: Inglese
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Serie: Scientific Computation, Libro 8 di 36. Libro 8 di 36 - Scientific Computation
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Taschenbuch. Condizione: Neu. Nonlinear Least Squares for Inverse Problems | Theoretical Foundations and Step-by-Step Guide for Applications | Guy Chavent | Taschenbuch | Scientific Computation | xiv | Englisch | 2012 | Springer | EAN 9789400730601 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 691…21 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Lingua: Inglese
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Serie: Scientific Computation, Libro 8 di 36. Libro 8 di 36 - Scientific Computation
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Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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- tratedtoseethatmyfriendsworki…ngonmodelingwhereproducingexistence, 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.
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Serie: Scientific Computation, Libro 8 di 36. Libro 8 di 36 - Scientific Computation
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Serie: Scientific Computation, Libro 8 di 36. Libro 8 di 36 - Scientific Computation
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Serie: Scientific Computation, Libro 8 di 36. Libro 8 di 36 - Scientific Computation
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.
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Taschenbuch. Condizione: 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- tratedtoseeth…atmyfriendsworkingonmodelingwhereproducingexistence, 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. 376 pp. Englisch.
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Serie: Scientific Computation, Libro 8 di 36. Libro 8 di 36 - Scientific Computation
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Condizione: 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 Le…ast Square problems.
Lingua: Inglese
Editore: Springer, 2012
Serie: Scientific Computation, Libro 8 di 36. Libro 8 di 36 - Scientific Computation
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Condizione: New. Print on Demand pp. 376 49:B&W 6.14 x 9.21 in or 234 x 156 mm (Royal 8vo) Perfect Bound on White w/Gloss Lam.
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Serie: Scientific Computation, Libro 8 di 36. Libro 8 di 36 - Scientific Computation
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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000
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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. 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- tratedtoseethatmy…friendsworkingonmodelingwhereproducingexistence, 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.Springer Nature Customer Service Center GmbH, Europaplatz 3, 69115 Heidelberg 376 pp. Englisch.
Lingua: Inglese
Editore: Springer, 2012
Serie: Scientific Computation, Libro 8 di 36. Libro 8 di 36 - Scientific Computation
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Condizione: New. PRINT ON DEMAND pp. 376.
