Numerical Methods for Stochastic Computations

A Spectral Method Approach

Nonfiction, Science & Nature, Mathematics, Applied, Computers, Advanced Computing, Computer Science, General Computing
Cover of the book Numerical Methods for Stochastic Computations by Dongbin Xiu, Princeton University Press
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Author: Dongbin Xiu ISBN: 9781400835348
Publisher: Princeton University Press Publication: July 1, 2010
Imprint: Princeton University Press Language: English
Author: Dongbin Xiu
ISBN: 9781400835348
Publisher: Princeton University Press
Publication: July 1, 2010
Imprint: Princeton University Press
Language: English

The@ first graduate-level textbook to focus on fundamental aspects of numerical methods for stochastic computations, this book describes the class of numerical methods based on generalized polynomial chaos (gPC). These fast, efficient, and accurate methods are an extension of the classical spectral methods of high-dimensional random spaces. Designed to simulate complex systems subject to random inputs, these methods are widely used in many areas of computer science and engineering.

The book introduces polynomial approximation theory and probability theory; describes the basic theory of gPC methods through numerical examples and rigorous development; details the procedure for converting stochastic equations into deterministic ones; using both the Galerkin and collocation approaches; and discusses the distinct differences and challenges arising from high-dimensional problems. The last section is devoted to the application of gPC methods to critical areas such as inverse problems and data assimilation.

Ideal for use by graduate students and researchers both in the classroom and for self-study, Numerical Methods for Stochastic Computations provides the required tools for in-depth research related to stochastic computations.

  • The first graduate-level textbook to focus on the fundamentals of numerical methods for stochastic computations
  • Ideal introduction for graduate courses or self-study
  • Fast, efficient, and accurate numerical methods
  • Polynomial approximation theory and probability theory included
  • Basic gPC methods illustrated through examples
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

The@ first graduate-level textbook to focus on fundamental aspects of numerical methods for stochastic computations, this book describes the class of numerical methods based on generalized polynomial chaos (gPC). These fast, efficient, and accurate methods are an extension of the classical spectral methods of high-dimensional random spaces. Designed to simulate complex systems subject to random inputs, these methods are widely used in many areas of computer science and engineering.

The book introduces polynomial approximation theory and probability theory; describes the basic theory of gPC methods through numerical examples and rigorous development; details the procedure for converting stochastic equations into deterministic ones; using both the Galerkin and collocation approaches; and discusses the distinct differences and challenges arising from high-dimensional problems. The last section is devoted to the application of gPC methods to critical areas such as inverse problems and data assimilation.

Ideal for use by graduate students and researchers both in the classroom and for self-study, Numerical Methods for Stochastic Computations provides the required tools for in-depth research related to stochastic computations.

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