Overview
- Aktuelles aus der Theorie der Markovketten
Part of the book series: Advanced Lectures in Mathematics (ALM)
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Table of contents (22 chapters)
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Front Matter
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Finite Markov chains (the background)
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Front Matter
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Rapidly mixing chains
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Front Matter
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Keywords
About this book
We start with a naive description of a Markov chain as a memoryless random walk on a finite set. This is complemented by a rigorous definition in the framework of probability theory, and then we develop the most important results from the theory of homogeneous Markov chains on finite state spaces.
Chains are called rapidly mixing if all of the associated walks, regardles of where they started, behave similarly already after comparitively few steps: it is impossible from observing the chain to get information on the starting position or the number of steps done so far. We will thoroughly study methods which have been proposed in the last decades to investigate this phenomenon.
A number of examples will be studied to indicate how the methods treated in this book can be applied.
Authors and Affiliations
About the author
Bibliographic Information
Book Title: Introduction to Markov Chains
Book Subtitle: With Special Emphasis on Rapid Mixing
Authors: Ehrhard Behrends
Series Title: Advanced Lectures in Mathematics
DOI: https://doi.org/10.1007/978-3-322-90157-6
Publisher: Vieweg+Teubner Verlag Wiesbaden
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eBook Packages: Springer Book Archive
Copyright Information: Springer Fachmedien Wiesbaden 2000
Softcover ISBN: 978-3-528-06986-5Published: 29 November 1999
eBook ISBN: 978-3-322-90157-6Published: 08 July 2014
Series ISSN: 0932-7134
Series E-ISSN: 2512-7039
Edition Number: 1
Number of Pages: IX, 234
Number of Illustrations: 6 b/w illustrations
Topics: Mathematics, general, Engineering, general