Finite Markov Chains and Algorithmic Applications
Finite Markov Chains and Algorithmic Applications
CAD$53.95
This text is ideal for advanced undergraduate or beginning graduate students. The author first develops the necessary background in probability theory and Markov chains before using it to study a range of randomized algorithms with important applications in optimization and other problems in computing. The book will appeal not only to mathematicians, but to students of computer science who will discover much useful material. This clear and concise introduction to the subject has numerous exercises that will help students to deepen their understanding.
- Clear and accessible introduction to algorithmic applications of Markov chains
- Relevant to computer scientists as well as mathematicians
Reviews & endorsements
"...extremely elegant...I am sure that students will find great pleasure in using the book--and that teachers will have the same pleasure in using it to prepare a course on the subject." Mathematics of Computation
"Here Haggstrom takes the beginning student from the first definitions concerning Markov chains even beyond Propp-Wilson to its refinementss and applications, all in just a hundred or so generously detailed pages. If an undergraduate reading this book comes away saying "I should have thought of that!" then the psychological barrier between school mathematics and research will have begun to break down. Few mathematical monographs provide a comparable opportunity. General readers; lower-division undergraduates through professionals." Choice
"[This series] is generally good....The use of examples to introduce the various algorithms is especially effective and makes the text easier to read." Mathematical Reviews
"The numerous examples perfectly well illustrate the more theoretical points. I am sure that students will find great pleasure in using the book-and that teachers will have the same pleasure in using it to prepare a course on the subject." Mathematics of Computation
Product details
June 2002Paperback
9780521890014
126 pages
228 × 153 × 8 mm
0.2kg
20 b/w illus.
Available
Table of Contents
- 1. Basics of probability theory
- 2. Markov chains
- 3. Computer simulation of Markov chains
- 4. Irreducible and aperiodic Markov chains
- 5. Stationary distributions
- 6. Reversible Markov chains
- 7. Markov chain Monte Carlo
- 8. Fast convergence of MCMC algorithms
- 9. Approximate counting
- 10. Propp-Wilson algorithm
- 11. Sandwiching
- 12. Propp-Wilson with read once randomness
- 13. Simulated annealing
- 14. Further reading.
