Stochastic tools in mathematics and science Alexandre J. Chorin, Ole H. Hald.

Chorin, Alexandre Joel.
Call Number
519.2 C45S
Author
Chorin, Alexandre Joel.
Title
Stochastic tools in mathematics and science Alexandre J. Chorin, Ole H. Hald.
Publication
New York : Springer Science + Business Media, Inc., c2006.
Physical Description
viii, 147 p. ; 24 cm.
Series
Surveys and tutorials in the applied mathematical sciences ; 1
Summary
This introductory book on probability-based modeling covers basic stochastic tools used in physics, chemistry, engineering and the life sciences. The topics include conditional expectations, stochastic processes, Brownian motion and its relation to partial differential equations, Langevin equations, the Liouville and Fokker-Planck equations, as well as Markov chain Monte Carlo algorithms, renormalization and dimensional reduction, and basic equilibrium and non-equilibrium statistical mechanics. The applications include data assimilation, prediction from partial data, spectral analysis, and turbulence. A noteworthy feature of the book is the systematic analysis of memory effects.
Added Author
Hald, Ole H.
Subject
STOCHASTIC PROCESSES.
Processus stochastiques.
Total Ratings: 0
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$a Stochastic tools in mathematics and science $c Alexandre J. Chorin, Ole H. Hald.
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$a viii, 147 p. ; $c 24 cm.
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$a Surveys and tutorials in the applied mathematical sciences ; $v 1
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$a Includes bibliographical references and index.
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$a This introductory book on probability-based modeling covers basic stochastic tools used in physics, chemistry, engineering and the life sciences. The topics include conditional expectations, stochastic processes, Brownian motion and its relation to partial differential equations, Langevin equations, the Liouville and Fokker-Planck equations, as well as Markov chain Monte Carlo algorithms, renormalization and dimensional reduction, and basic equilibrium and non-equilibrium statistical mechanics. The applications include data assimilation, prediction from partial data, spectral analysis, and turbulence. A noteworthy feature of the book is the systematic analysis of memory effects.
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Summary
This introductory book on probability-based modeling covers basic stochastic tools used in physics, chemistry, engineering and the life sciences. The topics include conditional expectations, stochastic processes, Brownian motion and its relation to partial differential equations, Langevin equations, the Liouville and Fokker-Planck equations, as well as Markov chain Monte Carlo algorithms, renormalization and dimensional reduction, and basic equilibrium and non-equilibrium statistical mechanics. The applications include data assimilation, prediction from partial data, spectral analysis, and turbulence. A noteworthy feature of the book is the systematic analysis of memory effects.
Subject
STOCHASTIC PROCESSES.
Processus stochastiques.