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Aggiungi al carrelloHardcover. Condizione: Brand New. 353 pages. 9.50x6.50x0.75 inches. In Stock.
Lingua: Inglese
Editore: Taylor & Francis Inc, Portland, 2018
ISBN 10: 1498764169 ISBN 13: 9781498764162
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Hardcover. Condizione: new. Hardcover. This book describes, in a basic way, the most useful and effective iterative solvers and appropriate preconditioning techniques for some of the most important classes of large and sparse linear systems.The solution of large and sparse linear systems is the most time-consuming part for most of the scientific computing simulations. Indeed, mathematical models become more and more accurate by including a greater volume of data, but this requires the solution of larger and harder algebraic systems. In recent years, research has focused on the efficient solution of large sparse and/or structured systems generated by the discretization of numerical models by using iterative solvers. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Lingua: Inglese
Editore: Taylor & Francis Inc, Portland, 2018
ISBN 10: 1498764169 ISBN 13: 9781498764162
Da: CitiRetail, Stevenage, Regno Unito
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Aggiungi al carrelloHardcover. Condizione: new. Hardcover. This book describes, in a basic way, the most useful and effective iterative solvers and appropriate preconditioning techniques for some of the most important classes of large and sparse linear systems.The solution of large and sparse linear systems is the most time-consuming part for most of the scientific computing simulations. Indeed, mathematical models become more and more accurate by including a greater volume of data, but this requires the solution of larger and harder algebraic systems. In recent years, research has focused on the efficient solution of large sparse and/or structured systems generated by the discretization of numerical models by using iterative solvers. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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Aggiungi al carrelloBuch. Condizione: Neu. Iterative Methods and Preconditioning for Large and Sparse Linear Systems with Applications | Daniele Bertaccini (u. a.) | Buch | Einband - fest (Hardcover) | Englisch | 2018 | Chapman and Hall/CRC | EAN 9781498764162 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.
Lingua: Inglese
Editore: Taylor & Francis Inc, Portland, 2018
ISBN 10: 1498764169 ISBN 13: 9781498764162
Da: AussieBookSeller, Truganina, VIC, Australia
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Aggiungi al carrelloHardcover. Condizione: new. Hardcover. This book describes, in a basic way, the most useful and effective iterative solvers and appropriate preconditioning techniques for some of the most important classes of large and sparse linear systems.The solution of large and sparse linear systems is the most time-consuming part for most of the scientific computing simulations. Indeed, mathematical models become more and more accurate by including a greater volume of data, but this requires the solution of larger and harder algebraic systems. In recent years, research has focused on the efficient solution of large sparse and/or structured systems generated by the discretization of numerical models by using iterative solvers. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 319,79
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Aggiungi al carrelloBuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book describes, in a basic way, the most useful and effective iterative solvers and appropriate preconditioning techniques for some of the most important classes of large and sparse linear systems.The solution of large and sparse linear systems is the most time-consuming part for most of the scientific computing simulations. Indeed, mathematical models become more and more accurate by including a greater volume of data, but this requires the solution of larger and harder algebraic systems. In recent years, research has focused on the efficient solution of large sparse and/or structured systems generated by the discretization of numerical models by using iterative solvers.