An Introduction to Computational Stochastic PDEs

Language: English

Published by Cambridge University Press, GB, 2014

0521728525 / 9780521728522

Series: Book 32 of 44 - Cambridge Texts in Applied Mathematics

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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.

Seller Inventory # LU-9780521728522

Title
An Introduction to Computational Stochastic PDEs
Author
Gabriel J. Lord, Catherine E. Powell, Tony Shardlow
Publisher
Cambridge University Press, GB
Publication year
2014
Condition
New
Binding
Paperback
Language
English
ISBN 10
0521728525
ISBN 13
9780521728522
Item weight
1,020 grams
Dimensions
17.78 x 2.54 x 24.77 cm
Series
Book 32 of 44: Cambridge Texts in Applied Mathematics

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