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Discrete Stochastic Processes and Applications

BuchKartoniert, Paperback
220 Seiten
Englisch
Springererschienen am13.04.20181st ed. 2018
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.mehr
Verfügbare Formate
BuchKartoniert, Paperback
EUR69,54
E-BookPDF1 - PDF WatermarkE-Book
EUR69,54

Produkt

KlappentextThis 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.
Zusammenfassung
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
Details
ISBN/GTIN978-3-319-74017-1
ProduktartBuch
EinbandartKartoniert, Paperback
Verlag
Erscheinungsjahr2018
Erscheinungsdatum13.04.2018
Auflage1st ed. 2018
ReiheUniversitext
Seiten220 Seiten
SpracheEnglisch
Gewicht371 g
IllustrationenXVII, 220 p. 3 illus.
Artikel-Nr.44243510

Inhalt/Kritik

Inhaltsverzeichnis
Preface.- I. Markov processes.- 1. Discrete time, countable space.- 2. Linear algebra and search engines.- 3. The Poisson process.- 4. Continuous time, discrete space.- 5. Examples.- II. Entropy and applications.- 6. Prelude: a user's guide to convexity.- 7. The basic quantities of information theory.- 8. An example of application: binary coding.- A. Some useful facts from calculus.- B. Some useful facts from probability.- C. Some useful facts from linear algebra.- D. An arithmetical lemma.- E. Table of exponential families.- References.- Index.mehr
Kritik
"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 Sandric, 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)mehr

Schlagworte

Autor

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.
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Collet, Jean-François