Stochastic Tools in Mathematics and Science (Texts in Applied Mathematics)
| Author | : | |
| Rating | : | 4.91 (982 Votes) |
| Asin | : | 1461469791 |
| Format Type | : | paperback |
| Number of Pages | : | 200 Pages |
| Publish Date | : | 2016-07-07 |
| Language | : | English |
DESCRIPTION:
"Fails half way between the math and the application" according to Litsios James. I am sad to give this book only three stars as I am a fan of one of its authors, Prof. Chorin, and have read many of his articles on numerical methods in fluid dynamics. But after having owned this book for some time now have having given it "my bedside attention"! I must conclude that this book fails what it tries to achieve. It tries to introduce mathematical stochastic tools without the rigor to a
There are additional figures and exercises. Review of earlier edition: "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." Mathematical Reviews, 2006. The book is based on lecture notes from a class that has attracted graduate and advanced undergraduate students from mathematics and from many other science departments at the University of California, Berkeley. The topics covered 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, basic statistical mechanics, and generalized Langevin equations and the Mori-Zwanzig formalism. Each chapter is followed by exercises. For this new edition the material has been thoroughly reorganized and updated, and new sections on scaling, sampling, filtering and data assimilation, based on recent research, have been added. "Stochastic Tools in Mathematics and Science" covers basic s
Each chapter is followed by exercises. The topics covered 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, basic statistical mechanics, and generalized Langevin equations and the Mori-Zwanzig formalism. The applications include sampling algorithms, data assimilation, prediction from partial data, spectral
Chorin is a professor of mathematics at the University of California, Berkeley who works in applied mathematics. He is known for his contributions to the field of Computational fluid dynamics. Ole Hald is a professor of mathematics at the University of California, Berkeley. Alexandre J.