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Convergence of Iterations for Linear Equations (Lectures in Mathematics. ETH Zürich) - Softcover

 
9783764328658: Convergence of Iterations for Linear Equations (Lectures in Mathematics. ETH Zürich)

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Assume that after preconditioning we are given a fixed point problem x = Lx + f (*) where L is a bounded linear operator which is not assumed to be symmetric and f is a given vector. The book discusses the convergence of Krylov subspace methods for solving fixed point problems (*), and focuses on the dynamical aspects of the iteration processes. For example, there are many similarities between the evolution of a Krylov subspace process and that of linear operator semigroups, in particular in the beginning of the iteration. A lifespan of an iteration might typically start with a fast but slowing phase. Such a behavior is sublinear in nature, and is essentially independent of whether the problem is singular or not. Then, for nonsingular problems, the iteration might run with a linear speed before a possible superlinear phase. All these phases are based on different mathematical mechanisms which the book outlines. The goal is to know how to precondition effectively, both in the case of "numerical linear algebra" (where one usually thinks of first fixing a finite dimensional problem to be solved) and in function spaces where the "preconditioning" corresponds to software which approximately solves the original problem.

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  • PublisherBirkhäuser
  • Publication date1993
  • ISBN 10 3764328657
  • ISBN 13 9783764328658
  • BindingPaperback
  • LanguageEnglish
  • Number of pages188

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9780817628659: Convergence of Iterations for Linear Equations (Lectures in Mathematics Eth Zurich)

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ISBN 10:  0817628657 ISBN 13:  9780817628659
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Assume that after preconditioning we are given a fixed point problem x = Lx + f (\*) where L is a bounded linear operator which is not assumed to be symmetric and f is a given vector. The book discusses the convergence of Krylov subspace methods for solving fixed point problems (\*), and focuses on the dynamical aspects of the iteration processes. For example, there are many similarities between the evolution of a Krylov subspace process and that of linear operator semigroups, in particular in the beginning of the iteration. A lifespan of an iteration might typically start with a fast but slowing phase. Such a behavior is sublinear in nature, and is essentially independent of whether the problem is singular or not. Then, for nonsingular problems, the iteration might run with a linear speed before a possible superlinear phase. All these phases are based on different mathematical mechanisms which the book outlines. The goal is to know how to precondition effectively, both in the case of 'numerical linear algebra' (where one usually thinks of first fixing a finite dimensional problem to be solved) and in function spaces where the 'preconditioning' corresponds to software which approximately solves the original problem. 180 pp. Englisch. Seller Inventory # 9783764328658

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Condition: Sehr gut. Zustand: Sehr gut - Gepflegter, sauberer Zustand. Aus der Auflösung einer renommierten Bibliothek. Kann Stempel beinhalten. | Seiten: 192 | Sprache: Englisch | Produktart: Bücher. Seller Inventory # 630071/202

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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - Assume that after preconditioning we are given a fixed point problem x = Lx + f (\*) where L is a bounded linear operator which is not assumed to be symmetric and f is a given vector. The book discusses the convergence of Krylov subspace methods for solving fixed point problems (\*), and focuses on the dynamical aspects of the iteration processes. For example, there are many similarities between the evolution of a Krylov subspace process and that of linear operator semigroups, in particular in the beginning of the iteration. A lifespan of an iteration might typically start with a fast but slowing phase. Such a behavior is sublinear in nature, and is essentially independent of whether the problem is singular or not. Then, for nonsingular problems, the iteration might run with a linear speed before a possible superlinear phase. All these phases are based on different mathematical mechanisms which the book outlines. The goal is to know how to precondition effectively, both in the case of 'numerical linear algebra' (where one usually thinks of first fixing a finite dimensional problem to be solved) and in function spaces where the 'preconditioning' corresponds to software which approximately solves the original problem. Seller Inventory # 9783764328658

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Kartoniert / Broschiert. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Assume that after preconditioning we are given a fixed point problem x = Lx + f (*) where L is a bounded linear operator which is not assumed to be symmetric and f is a given vector. The book discusses the convergence of Krylov subspace methods for solving . Seller Inventory # 5279007

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