Functional Analysis for Probability and Stochastic Processes

Functional Analysis for Probability and Stochastic Processes

Author: Adam Bobrowski

Publisher: Cambridge University Press

Published: 2005-08-11

Total Pages: 416

ISBN-13: 9780521831666

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This text presents selected areas of functional analysis that can facilitate an understanding of ideas in probability and stochastic processes. Topics covered include basic Hilbert and Banach spaces, weak topologies and Banach algebras, and the theory ofsemigroups of bounded linear operators.


Dirichlet Forms and Symmetric Markov Processes

Dirichlet Forms and Symmetric Markov Processes

Author: Masatoshi Fukushima

Publisher: Walter de Gruyter

Published: 2011

Total Pages: 501

ISBN-13: 3110218089

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Since the publication of the first edition in 1994, this book has attracted constant interests from readers and is by now regarded as a standard reference for the theory of Dirichlet forms. For the present second edition, the authors not only revise


An Introduction to Markov Processes

An Introduction to Markov Processes

Author: Daniel W. Stroock

Publisher: Springer Science & Business Media

Published: 2005-03-30

Total Pages: 196

ISBN-13: 9783540234517

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Provides a more accessible introduction than other books on Markov processes by emphasizing the structure of the subject and avoiding sophisticated measure theory Leads the reader to a rigorous understanding of basic theory


Probability and Stochastics

Probability and Stochastics

Author: Erhan Çınlar

Publisher: Springer Science & Business Media

Published: 2011-02-21

Total Pages: 567

ISBN-13: 0387878599

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This text is an introduction to the modern theory and applications of probability and stochastics. The style and coverage is geared towards the theory of stochastic processes, but with some attention to the applications. In many instances the gist of the problem is introduced in practical, everyday language and then is made precise in mathematical form. The first four chapters are on probability theory: measure and integration, probability spaces, conditional expectations, and the classical limit theorems. There follows chapters on martingales, Poisson random measures, Levy Processes, Brownian motion, and Markov Processes. Special attention is paid to Poisson random measures and their roles in regulating the excursions of Brownian motion and the jumps of Levy and Markov processes. Each chapter has a large number of varied examples and exercises. The book is based on the author’s lecture notes in courses offered over the years at Princeton University. These courses attracted graduate students from engineering, economics, physics, computer sciences, and mathematics. Erhan Cinlar has received many awards for excellence in teaching, including the President’s Award for Distinguished Teaching at Princeton University. His research interests include theories of Markov processes, point processes, stochastic calculus, and stochastic flows. The book is full of insights and observations that only a lifetime researcher in probability can have, all told in a lucid yet precise style.


Multiparameter Processes

Multiparameter Processes

Author: Davar Khoshnevisan

Publisher: Springer Science & Business Media

Published: 2006-04-10

Total Pages: 590

ISBN-13: 0387216316

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Self-contained presentation: from elementary material to state-of-the-art research; Much of the theory in book-form for the first time; Connections are made between probability and other areas of mathematics, engineering and mathematical physics


Markov Processes, Semigroups, and Generators

Markov Processes, Semigroups, and Generators

Author: Vassili N. Kolokoltsov

Publisher: Walter de Gruyter

Published: 2011

Total Pages: 449

ISBN-13: 3110250101

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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