Verlag: Cambridge University Press, 2014
ISBN 10: 0521728525 ISBN 13: 9780521728522
Sprache: Englisch
Anbieter: Better World Books, Mishawaka, IN, USA
EUR 55,87
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In den WarenkorbZustand: Very Good. Former library book; may include library markings. Used book that is in excellent condition. May show signs of wear or have minor defects.
Verlag: Cambridge University Press, 2014
ISBN 10: 0521728525 ISBN 13: 9780521728522
Sprache: Englisch
Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes Königreich
EUR 74,69
Währung umrechnenAnzahl: Mehr als 20 verfügbar
In den WarenkorbZustand: New. In.
Anbieter: Revaluation Books, Exeter, Vereinigtes Königreich
EUR 104,08
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In den WarenkorbPaperback. Zustand: Brand New. 503 pages. 9.75x7.00x1.00 inches. In Stock.
Verlag: Cambridge University Press, 2014
ISBN 10: 0521728525 ISBN 13: 9780521728522
Sprache: Englisch
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
EUR 148,44
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In den WarenkorbTaschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book gives a comprehensive introduction to numerical methods and analysis of stochastic processes, random fields and stochastic differential equations, and offers graduate students and researchers powerful tools for understanding uncertainty quantification for risk analysis. Coverage includes traditional stochastic ODEs with white noise forcing, strong and weak approximation, and the multi-level Monte Carlo method. Later chapters apply the theory of random fields to the numerical solution of elliptic PDEs with correlated random data, discuss the Monte Carlo method, and introduce stochastic Galerkin finite-element methods. Finally, stochastic parabolic PDEs are developed. Assuming little previous exposure to probability and statistics, theory is developed in tandem with state-of-the-art computational methods through worked examples, exercises, theorems and proofs. The set of MATLAB® codes included (and downloadable) allows readers to perform computations themselves and solve the test problems discussed. Practical examples are drawn from finance, mathematical biology, neuroscience, fluid flow modelling and materials science.
Verlag: Cambridge University Press, 2014
ISBN 10: 0521899907 ISBN 13: 9780521899901
Sprache: Englisch
Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes Königreich
EUR 145,86
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In den WarenkorbZustand: New. In.
Verlag: Cambridge University Press, 2014
ISBN 10: 0521899907 ISBN 13: 9780521899901
Sprache: Englisch
Anbieter: Majestic Books, Hounslow, Vereinigtes Königreich
EUR 185,71
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In den WarenkorbZustand: New. pp. 520 123 Illus. (16 Col.).
Anbieter: Revaluation Books, Exeter, Vereinigtes Königreich
EUR 218,36
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In den WarenkorbHardcover. Zustand: Brand New. 503 pages. 10.00x7.25x1.00 inches. In Stock.
Verlag: Cambridge University Press, 2014
ISBN 10: 0521899907 ISBN 13: 9780521899901
Sprache: Englisch
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
EUR 256,82
Währung umrechnenAnzahl: 1 verfügbar
In den WarenkorbBuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book gives a comprehensive introduction to numerical methods and analysis of stochastic processes, random fields and stochastic differential equations, and offers graduate students and researchers powerful tools for understanding uncertainty quantification for risk analysis. Coverage includes traditional stochastic ODEs with white noise forcing, strong and weak approximation, and the multi-level Monte Carlo method. Later chapters apply the theory of random fields to the numerical solution of elliptic PDEs with correlated random data, discuss the Monte Carlo method, and introduce stochastic Galerkin finite-element methods. Finally, stochastic parabolic PDEs are developed. Assuming little previous exposure to probability and statistics, theory is developed in tandem with state-of-the-art computational methods through worked examples, exercises, theorems and proofs. The set of MATLAB® codes included (and downloadable) allows readers to perform computations themselves and solve the test problems discussed. Practical examples are drawn from finance, mathematical biology, neuroscience, fluid flow modelling and materials science.