Stochastic Tools in Mathematics and Science

Author:   Alexandre J. Chorin ,  Ole H. Hald
Publisher:   Springer-Verlag New York Inc.
Edition:   2nd ed. 2009
Volume:   No. 1
ISBN:  

9781441910011


Pages:   174
Publication Date:   01 August 2009
Format:   Paperback
Availability:   In Print   Availability explained
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Stochastic Tools in Mathematics and Science


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Overview

This introduction to probability-based modeling covers basic stochastic tools used in physics, chemistry, engineering and the life sciences. Topics covered include conditional expectations, stochastic processes, Langevin equations, and Markov chain Monte Carlo algorithms. The applications include data assimilation, prediction from partial data, spectral analysis and turbulence. A special feature is the systematic analysis of memory effects.

Full Product Details

Author:   Alexandre J. Chorin ,  Ole H. Hald
Publisher:   Springer-Verlag New York Inc.
Imprint:   Springer-Verlag New York Inc.
Edition:   2nd ed. 2009
Volume:   No. 1
Dimensions:   Width: 15.60cm , Height: 0.90cm , Length: 23.40cm
Weight:   0.560kg
ISBN:  

9781441910011


ISBN 10:   1441910018
Pages:   174
Publication Date:   01 August 2009
Audience:   College/higher education ,  Professional and scholarly ,  Postgraduate, Research & Scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Out of Print
Availability:   In Print   Availability explained
Limited stock is available. It will be ordered for you and shipped pending supplier's limited stock.

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Reviews

From the reviews of the first edition: The book is well-written and provides a very useful introduction to various areas of applications of stochastic processes. (Evelyn Buckwar, Zentralblatt MATH, Vol. 1086, 2006) The authors write ! that this book is based on lecture notes for graduate courses on 'the stochastic methods of applied mathematics'. Their aim is ! to show various applications of probability to mathematics students and, on the other hand, to introduce nonmathematical students to the general ideas of probabilistic methods. ! This is an excellent concise textbook which can be used for self-study by graduate and advanced undergraduate students and as a recommended textbook for an introductory course on probabilistic tools in science. (Mikhail V. Tretyakov, Mathematical Reviews, Issue 2006 j) Chorin and Hald provide excellent explanations with considerable insight and deep mathematical understanding, especially toward the end of the book in the context of simplified versions of the famous statistical mechanics models of Isign and of Mori and Zwanzig. (SIAM Review)


From the reviews: The book is well-written and provides a very useful introduction to various areas of applications of stochastic processes. (Evelyn Buckwar, Zentralblatt MATH, Vol. 1086, 2006) The authors write ... that this book is based on lecture notes for graduate courses on 'the stochastic methods of applied mathematics'. Their aim is ... to show various applications of probability to mathematics students and, on the other hand, to introduce nonmathematical students to the general ideas of probabilistic methods. ... This is an excellent concise textbook which can be used for self-study by graduate and advanced undergraduate students and as a recommended textbook for an introductory course on probabilistic tools in science. (Mikhail V. Tretyakov, Mathematical Reviews, Issue 2006 j) Chorin and Hald provide excellent explanations with considerable insight and deep mathematical understanding, especially toward the end of the book in the context of simplified versions of the famous statistical mechanics models of Isign and of Mori and Zwanzig. (SIAM Review) From the reviews of the second edition: In the second edition of the book by Alexandre J. Chorin and Ole H. Hald many parts of the text have been rewritten in order to clarify the presentation. ... The authors have added a short discussion on Feynman diagrams to the section on Wiener integrals. ... Also new exercises and figures have been added to the text. The new topics make the book even more useful as an introduction to stochastic modeling in the natural sciences and will certainly be appreciated by the readers. (H. M. Mai, Zentralblatt MATH, Vol. 1184, 2010)


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