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Discrete Stochastic Processes and Applications

  • Textbook
  • © 2018

Overview

  • 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
  • Presents an engaging treatment of entropy
  • Reader develops solid probabilistic intuition without the need for a course in measure theory

Part of the book series: Universitext (UTX)

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Table of contents (8 chapters)

  1. Markov processes

  2. Entropy and applications

Keywords

About this book

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.

Reviews

“This textbook is a very nice introductory material to the subjects of discrete and continuous-time Markov chains, and information theory with applications to binary coding. It is nicely written and it provides a self-contained treatment of the topics.” (Nikola Sandrić, zbMATH 1431.60001, 2020)

“The ideal audience for this text would be students or practitioners in that sweet spot where mathematical rigor is important … . an excellent reference for Markov Chain theory for an instructor struggling to determine how much rigor to introduce into a course on Markov chains.” (John K. McSweeney, MAA Reviews, September 22, 2019)

Authors and Affiliations

  • Laboratoire J.A. Dieudonné, Université de Nice Sophia-Antipolis, Nice Cedex 02, France

    Jean-François Collet

About the author

Jean-François Collet received his PhD from the University of Bloomington in 1992 and has been Maître de Conférences at the Laboratoire J.A. Dieudonné, Université de Nice Sophia-Antipolis since 1993. Professor Collet’s research interests include Partial Differential Equations and Information theory.

Bibliographic Information

  • Book Title: Discrete Stochastic Processes and Applications

  • Authors: Jean-François Collet

  • Series Title: Universitext

  • DOI: https://doi.org/10.1007/978-3-319-74018-8

  • Publisher: Springer Cham

  • eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)

  • Copyright Information: Springer International Publishing AG, part of Springer Nature 2018

  • Softcover ISBN: 978-3-319-74017-1Published: 13 April 2018

  • eBook ISBN: 978-3-319-74018-8Published: 05 April 2018

  • Series ISSN: 0172-5939

  • Series E-ISSN: 2191-6675

  • Edition Number: 1

  • Number of Pages: XVII, 220

  • Number of Illustrations: 3 b/w illustrations

  • Topics: Probability Theory and Stochastic Processes

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