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Title: AN INTRODUCTION TO COMPUTATIONAL STOCHASTIC PDES
By: Gabriel J. Lord, Catherine Elizabeth Powell, Tony Shardlow
Format: Hardback

List price: £111.00
Our price: £97.13
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ISBN 10: 0521899907
ISBN 13: 9780521899901
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Publisher: CAMBRIDGE UNIVERSITY PRESS
Pub. date: 31 July, 2014
Series: Cambridge Texts in Applied Mathematics 50
Pages: 516
Description: This book offers a practical presentation of stochastic partial differential equations arising in physical applications and their numerical approximation.
Synopsis: 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(R) 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.
Illustrations: 107 b/w illus. 16 colour illus. 222 exercises
Publication: UK
Imprint: Cambridge University Press
Returns: Returnable
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