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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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.
"Sobre este título" puede pertenecer a otra edición de este libro.
Librería: Better World Books, Mishawaka, IN, Estados Unidos de America
Condición: Good. Former library copy. Pages intact with minimal writing/highlighting. The binding may be loose and creased. Dust jackets/supplements are not included. Includes library markings. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good. Nº de ref. del artículo: 55588673-6
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Librería: Antiquariat Bookfarm, Löbnitz, Alemania
Softcover. VII, 177 S. Ex-library with stamp and library-signature. GOOD condition, some traces of use. C-03513 3764328657 Sprache: Englisch Gewicht in Gramm: 550. Nº de ref. del artículo: 2489426
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Librería: Books Puddle, New York, NY, Estados Unidos de America
Condición: New. pp. 192. Nº de ref. del artículo: 263101825
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Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
Taschenbuch. Condición: 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. Nº de ref. del artículo: 9783764328658
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Librería: Majestic Books, Hounslow, Reino Unido
Condición: New. Print on Demand pp. 192 67:B&W 6.69 x 9.61 in or 244 x 170 mm (Pinched Crown) Perfect Bound on White w/Gloss Lam. Nº de ref. del artículo: 5827422
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Librería: Biblios, Frankfurt am main, HESSE, Alemania
Condición: New. PRINT ON DEMAND pp. 192. Nº de ref. del artículo: 183101835
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Librería: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Irlanda
Condición: New. Discussing the convergence of Krylov subspace methods for solving fixed point problems, this work focuses on the dynamical aspects of the iteration processes and outlines all the phases of a lifespan of an iteration. Series: Lectures in Mathematics. ETH Zurich. Num Pages: 188 pages, 15 black & white illustrations, biography. BIC Classification: PBK; PBT. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly. Dimension: 244 x 170 x 10. Weight in Grams: 316. . 1993. 1993rd Edition. paperback. . . . . Nº de ref. del artículo: V9783764328658
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Librería: moluna, Greven, Alemania
Condición: 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 . Nº de ref. del artículo: 5279007
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