Dekorationsartikel gehören nicht zum Leistungsumfang.
Sprache:
Englisch
54,80 €
Versandkostenfrei per Post / DHL
Lieferzeit 4-7 Werktage
Kategorien:
Beschreibung
This text presents selected applications of discrete-time stochastic processes that involve random interactions and algorithms, and revolve around the Markov property. It covers recurrence properties of (excited) random walks, convergence and mixing of Markov chains, distribution modeling using phase-type distributions, applications to search engines and probabilistic automata, and an introduction to the Ising model used in statistical physics. Applications to data science are also considered via hidden Markov models and Markov decision processes. A total of 32 exercises and 17 longer problems are provided with detailed solutions and cover various topics of interest, including statistical learning.
This text presents selected applications of discrete-time stochastic processes that involve random interactions and algorithms, and revolve around the Markov property. It covers recurrence properties of (excited) random walks, convergence and mixing of Markov chains, distribution modeling using phase-type distributions, applications to search engines and probabilistic automata, and an introduction to the Ising model used in statistical physics. Applications to data science are also considered via hidden Markov models and Markov decision processes. A total of 32 exercises and 17 longer problems are provided with detailed solutions and cover various topics of interest, including statistical learning.
Über den Autor
Nicolas Privault received a PhD degree from the University of Paris VI, France. He was with the University of Evry, France, the University of La Rochelle, France, and the University of Poitiers, France. He is currently a Professor with the School of Physical and Mathematical Sciences, Nanyang Technological University, Singapore. His research interests are in the areas of stochastic analysis and its applications.
Inhaltsverzeichnis
- 1. A Summary of Markov Chains.- 2. Phase-Type Distributions.- 3. Synchronizing Automata.- 4. Random Walks and Recurrence.- 5. Cookie-Excited Random Walks.- 6. Convergence to Equilibrium.- 7. The Ising Model.- 8. Search Engines.- 9. Hidden Markov Model.- 10. Markov Decision Processes.
Details
| Erscheinungsjahr: | 2024 |
|---|---|
| Fachbereich: | Wahrscheinlichkeitstheorie |
| Genre: | Mathematik, Medizin, Naturwissenschaften, Technik |
| Rubrik: | Naturwissenschaften & Technik |
| Medium: | Taschenbuch |
| Reihe: | Springer Undergraduate Mathematics Series |
| Inhalt: |
xii
288 S. 14 s/w Illustr. 130 farbige Illustr. 288 p. 144 illus. 130 illus. in color. |
| ISBN-13: | 9783031658198 |
| ISBN-10: | 3031658191 |
| Sprache: | Englisch |
| Einband: | Kartoniert / Broschiert |
| Autor: | Privault, Nicolas |
| Hersteller: |
Springer
Springer International Publishing AG Springer Undergraduate Mathematics Series |
| Verantwortliche Person für die EU: | Springer Verlag GmbH, Tiergartenstr. 17, D-69121 Heidelberg, juergen.hartmann@springer.com |
| Maße: | 235 x 155 x 17 mm |
| Von/Mit: | Nicolas Privault |
| Erscheinungsdatum: | 08.10.2024 |
| Gewicht: | 0,458 kg |