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Uncertainty quantification and stochastic modeling with Matlab / Eduardo Souza de Cursi and Rubens Sampaio.

By: Contributor(s): Series: Numerical methods in engineeringPublication details: London : ISTE Press, 2015.Description: xiii, 442 p. : illustrations ; 24 cmISBN:
  • 9781785480058
Subject(s): DDC classification:
  • 519.2 23 C977
Contents:
1. Elements of probability theory and stochastic processes -- 2.Maximum entropy and information -- 3. Representation of random variables -- 4. Linear algebraic equations under uncertainty -- 5. Nonlinear algebraic equations involving random parameters -- 6. Differential equations under uncertainty -- 7. Optimization under uncertainty -- 8. Reliability-based optimization.
Summary: This book gives a unified, practical and comprehensive presentation of the main techniques used for the characterization of the effect of uncertainty on numerical models and on their exploitation in numerical problems. In particular, applications to linear and nonlinear systems of equations, differential equations, optimization and reliability are presented. Applications of stochastic methods to deal with deterministic numerical problems are also discussed. Matlabª illustrates the implementation of these methods and makes the book suitable as a textbook and for self-study.
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Includes bibliographical references and index.

1. Elements of probability theory and stochastic processes --
2.Maximum entropy and information --
3. Representation of random variables --
4. Linear algebraic equations under uncertainty --
5. Nonlinear algebraic equations involving random parameters --
6. Differential equations under uncertainty --
7. Optimization under uncertainty --
8. Reliability-based optimization.

This book gives a unified, practical and comprehensive presentation of the main techniques used for the characterization of the effect of uncertainty on numerical models and on their exploitation in numerical problems. In particular, applications to linear and nonlinear systems of equations, differential equations, optimization and reliability are presented. Applications of stochastic methods to deal with deterministic numerical problems are also discussed. Matlabª illustrates the implementation of these methods and makes the book suitable as a textbook and for self-study.

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