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Deterministic and Stochastic Error Bounds in Numerical Analysis: 1349 (Lecture Notes in Mathematics, 1349) - Softcover

 
9783540503682: Deterministic and Stochastic Error Bounds in Numerical Analysis: 1349 (Lecture Notes in Mathematics, 1349)

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In these notes different deterministic and stochastic error bounds of numerical analysis are investigated. For many computational problems we have only partial information (such as n function values) and consequently they can only be solved with uncertainty in the answer. Optimal methods and optimal error bounds are sought if only the type of information is indicated. First, worst case error bounds and their relation to the theory of n-widths are considered; special problems such approximation, optimization, and integration for different function classes are studied and adaptive and nonadaptive methods are compared. Deterministic (worst case) error bounds are often unrealistic and should be complemented by different average error bounds. The error of Monte Carlo methods and the average error of deterministic methods are discussed as are the conceptual difficulties of different average errors. An appendix deals with the existence and uniqueness of optimal methods. This book is an introduction to the area and also a research monograph containing new results. It is addressd to a general mathematical audience as well as specialists in the areas of numerical analysis and approximation theory (especially optimal recovery and information-based complexity).

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Novak, Erich et al
Published by Springer, 1988
ISBN 10: 3540503684 ISBN 13: 9783540503682
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Condition: Fair. Volume 1349. This is an ex-library book and may have the usual library/used-book markings inside.This book has soft covers. In fair condition, suitable as a study copy. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,350grams, ISBN:3540503684. Seller Inventory # 7094531

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Softcover. Ex-library with stamp and library-signature. GOOD condition, some traces of use. Ehem. Bibliotheksexemplar mit Signatur und Stempel. GUTER Zustand, ein paar Gebrauchsspuren. C-04769 3540503684 Sprache: Englisch Gewicht in Gramm: 550. Seller Inventory # 2491010

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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -In these notes different deterministic and stochastic error bounds of numerical analysis are investigated. For many computational problems we have only partial information (such as n function values) and consequently they can only be solved with uncertainty in the answer. Optimal methods and optimal error bounds are sought if only the type of information is indicated. First, worst case error bounds and their relation to the theory of n-widths are considered; special problems such approximation, optimization, and integration for different function classes are studied and adaptive and nonadaptive methods are compared. Deterministic (worst case) error bounds are often unrealistic and should be complemented by different average error bounds. The error of Monte Carlo methods and the average error of deterministic methods are discussed as are the conceptual difficulties of different average errors. An appendix deals with the existence and uniqueness of optimal methods. This book is an introduction to the area and also a research monograph containing new results. It is addressd to a general mathematical audience as well as specialists in the areas of numerical analysis and approximation theory (especially optimal recovery and information-based complexity). 128 pp. Englisch. Seller Inventory # 9783540503682

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Paperback. Condition: Very Good. Berlin, Heidelberg, New York: Springer-Verlag, 1988. 113 pp. 24 x 16.5 cm. Stiff paper wrappers printed in yellow and black. Very faint bump to head of spine. Mild to moderate age toning to text block; interior clean and unmarked. Binding firm with no creases or cracks. Soft Cover. Very Good. Seller Inventory # 626104

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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - In these notes different deterministic and stochastic error bounds of numerical analysis are investigated. For many computational problems we have only partial information (such as n function values) and consequently they can only be solved with uncertainty in the answer. Optimal methods and optimal error bounds are sought if only the type of information is indicated. First, worst case error bounds and their relation to the theory of n-widths are considered; special problems such approximation, optimization, and integration for different function classes are studied and adaptive and nonadaptive methods are compared. Deterministic (worst case) error bounds are often unrealistic and should be complemented by different average error bounds. The error of Monte Carlo methods and the average error of deterministic methods are discussed as are the conceptual difficulties of different average errors. An appendix deals with the existence and uniqueness of optimal methods. This book is an introduction to the area and also a research monograph containing new results. It is addressd to a general mathematical audience as well as specialists in the areas of numerical analysis and approximation theory (especially optimal recovery and information-based complexity). Seller Inventory # 9783540503682

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