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Markov processes, semigroups, and generators /

This work offers a highly useful, well developed reference on Markov processes, the universal model for random processes and evolutions. The wide range of applications, in exact sciences as well as in other areas like social studies, require a volume that offers a refresher on fundamentals before co...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Kolokolʹt͡sov, V. N. (Vasiliĭ Nikitich)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Berlin ; New York : De Gruyter, ©2011.
Colección:De Gruyter studies in mathematics ; 38.
Temas:
Acceso en línea:Texto completo

MARC

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100 1 |a Kolokolʹt͡sov, V. N.  |q (Vasiliĭ Nikitich) 
245 1 0 |a Markov processes, semigroups, and generators /  |c Vassili N. Kolokoltsov. 
260 |a Berlin ;  |a New York :  |b De Gruyter,  |c ©2011. 
300 |a 1 online resource (xviii, 430 pages) :  |b illustrations 
336 |a text  |b txt  |2 rdacontent 
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490 1 |a De Gruyter studies in mathematics,  |x 0179-0986 ;  |v 38 
504 |a Includes bibliographical references and index. 
505 0 |6 880-01  |a pt. 1. Introduction to stochastic analysis -- pt. 2. Markov processes and beyond. 
520 |6 880-02  |a This work offers a highly useful, well developed reference on Markov processes, the universal model for random processes and evolutions. The wide range of applications, in exact sciences as well as in other areas like social studies, require a volume that offers a refresher on fundamentals before conveying the Markov processes and examples for applications. This work does just that, and with the necessary mathematical rigor. 
588 0 |a Print version record. 
546 |a In English. 
590 |a eBooks on EBSCOhost  |b EBSCO eBook Subscription Academic Collection - Worldwide 
650 0 |a Markov processes. 
650 0 |a Semigroups. 
650 0 |a Group theory  |x Generators. 
650 4 |a Markov Processes, Semigroups, random processes. 
650 6 |a Processus de Markov. 
650 6 |a Semi-groupes. 
650 6 |a Théorie des groupes  |x Générateurs. 
650 7 |a MATHEMATICS  |x Probability & Statistics  |x Stochastic Processes.  |2 bisacsh 
650 7 |a Group theory  |x Generators.  |2 fast  |0 (OCoLC)fst00948524 
650 7 |a Markov processes.  |2 fast  |0 (OCoLC)fst01010347 
650 7 |a Semigroups.  |2 fast  |0 (OCoLC)fst01112267 
650 7 |a Markov-Prozess  |2 gnd 
776 0 8 |i Print version:  |a Kolokolʹt͡sov, V.N. (Vasiliĭ Nikitich).  |t Markov processes, semigroups, and generators.  |d Berlin ; New York : De Gruyter, ©2011  |w (DLC) 2010050783 
830 0 |a De Gruyter studies in mathematics ;  |v 38.  |x 0179-0986 
856 4 0 |u https://ebsco.uam.elogim.com/login.aspx?direct=true&scope=site&db=nlebk&AN=388244  |z Texto completo 
880 0 0 |6 505-01/(S  |t Frontmatter --  |t Preface --  |t Notations --  |t Standard abbreviations --  |t Contents --  |t I Introduction to stochastic analysis --  |t 1 Tools from probability and analysis --  |t 2 Brownian motion (BM) --  |t 3 Markov processes and martingales --  |t 4 SDE, ΨDE and martingale problems --  |t II Markov processes and beyond --  |t 5 Processes in Euclidean spaces --  |t 6 Processes in domains with a boundary --  |t 7 Heat kernels for stable-like processes --  |t 8 CTRW and fractional dynamics --  |t 9 Complex Markov chains and Feynman integral --  |t Bibliography --  |t Index. 
880 |6 520-02/(S  |a 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. 
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