书目名称 | Feynman-Kac Formulae | 副标题 | Genealogical and Int | 编辑 | Pierre Moral | 视频video | | 概述 | Takes readers in a clear and progressive format from simple to recent and advanced topics in pure and applied probability such as contraction and annealed properties of non linear semi-groups, functio | 丛书名称 | Probability and Its Applications | 图书封面 |  | 描述 | The central theme of this book concerns Feynman-Kac path distributions, interacting particle systems, and genealogical tree based models. This re cent theory has been stimulated from different directions including biology, physics, probability, and statistics, as well as from many branches in engi neering science, such as signal processing, telecommunications, and network analysis. Over the last decade, this subject has matured in ways that make it more complete and beautiful to learn and to use. The objective of this book is to provide a detailed and self-contained discussion on these connec tions and the different aspects of this subject. Although particle methods and Feynman-Kac models owe their origins to physics and statistical me chanics, particularly to the kinetic theory of fluid and gases, this book can be read without any specific knowledge in these fields. I have tried to make this book accessible for senior undergraduate students having some familiarity with the theory of stochastic processes to advanced postgradu ate students as well as researchers and engineers in mathematics, statistics, physics, biology and engineering. I have also tried to give an "expose" of | 出版日期 | Book 2004 | 关键词 | Feynman-Kac formula; Markov chain; Markov kernel; Markov process; Monte Carlo method; Statistical Physics | 版次 | 1 | doi | https://doi.org/10.1007/978-1-4684-9393-1 | isbn_softcover | 978-1-4419-1902-1 | isbn_ebook | 978-1-4684-9393-1Series ISSN 1431-7028 | issn_series | 1431-7028 | copyright | Springer Science+Business Media New York 2004 |
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