| 书目名称 | Discrete Stochastic Processes and Applications |
| 编辑 | Jean-François Collet |
| 视频video | |
| 概述 | Provides applications to Markov processes, coding/information theory, population dynamics, and search engine design.Ideal for a newly designed introductory course to probability and information theory |
| 丛书名称 | Universitext |
| 图书封面 |  |
| 描述 | .This unique text for beginning graduate students gives a self-contained introduction to the mathematical properties of stochastics and presents their applications to Markov processes, coding theory, population dynamics, and search engine design. The book is ideal for a newly designed course in an introduction to probability and information theory. Prerequisites include working knowledge of linear algebra, calculus, and probability theory. The first part of the text focuses on the rigorous theory of Markov processes on countable spaces (Markov chains) and provides the basis to developing solid probabilistic intuition without the need for a course in measure theory. The approach taken is gradual beginning with the case of discrete time and moving on to that of continuous time. The second part of this text is more applied; its core introduces various uses of convexity in probability and presents a nice treatment of entropy.. |
| 出版日期 | Textbook 2018 |
| 关键词 | Markov processes; Brownian motion; Perron-Frobenius theorem; Poisson process; information theory; search |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-319-74018-8 |
| isbn_softcover | 978-3-319-74017-1 |
| isbn_ebook | 978-3-319-74018-8Series ISSN 0172-5939 Series E-ISSN 2191-6675 |
| issn_series | 0172-5939 |
| copyright | Springer International Publishing AG, part of Springer Nature 2018 |
发表于 2025-3-21 17:05:16
