Markov Processes, Semigroups and Generators
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Vassili N. Kolokoltsov
About this book
Markov processes represent a universal model for a large variety of real life random evolutions. The wide flow of new ideas, tools, methods and applications constantly pours into the ever-growing stream of research on Markov processes that rapidly spreads over new fields of natural and social sciences, creating new streamlined logical paths to its turbulent boundary. Even if a given process is not Markov, it can be often inserted into a larger Markov one (Markovianization procedure) by including the key historic parameters into the state space.
This monograph gives a concise, but systematic and self-contained, exposition of the essentials of Markov processes, together with recent achievements, working from the "physical picture" - a formal pre-generator, and stressing the interplay between probabilistic (stochastic differential equations) and analytic (semigroups) tools.
The book will be useful to students and researchers. Part I can be used for a one-semester course on Brownian motion, Lévy and Markov processes, or on probabilistic methods for PDE. Part II mainly contains the author's research on Markov processes.
From the contents:
- Tools from Probability and Analysis
- Brownian motion
- Markov processes and martingales
- SDE, ψDE and martingale problems
- Processes in Euclidean spaces
- Processes in domains with a boundary
- Heat kernels for stable-like processes
- Continuous-time random walks and fractional dynamics
- Complex chains and Feynman integral
- Offers a first part on basic concepts of probability theory
- Then builds on that by conveying material on generators for stable-like processes and Levy processes
- A third part offers various applications
- Easy to follow presentation
- With examples and exercises, so useable as secondary reading for courses
Author / Editor information
Vassili N. Kolokoltsov, University of Warwick, UK.
Reviews
Anatoly N. Kochubei, Zentralblatt für Mathematik
Topics
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Frontmatter
I -
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Preface
VII -
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Notations
XI -
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Standard abbreviations
XIV -
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Contents
XV - I Introduction to stochastic analysis
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1 Tools from probability and analysis
3 -
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2 Brownian motion (BM)
58 -
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3 Markov processes and martingales
94 -
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4 SDE, ΨDE and martingale problems
152 - II Markov processes and beyond
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5 Processes in Euclidean spaces
204 -
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6 Processes in domains with a boundary
270 -
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7 Heat kernels for stable-like processes
310 -
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8 CTRW and fractional dynamics
351 -
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9 Complex Markov chains and Feynman integral
373 -
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Bibliography
403 -
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Index
425
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