Real Analysis Methods for Markov Processes
Author: Kazuaki Taira
Publisher: Springer Nature
Published:
Total Pages: 749
ISBN-13: 9819736595
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Real Analysis and Probability
Author: R. M. Dudley
Publisher: Cambridge University Press
Published: 2002-10-14
Total Pages: 570
ISBN-13: 9780521007542
DOWNLOAD EBOOKThis classic text offers a clear exposition of modern probability theory.
Boundary Value Problems and Markov Processes
Author: Kazuaki Taira
Publisher: Springer Nature
Published: 2020-07-01
Total Pages: 502
ISBN-13: 3030487881
DOWNLOAD EBOOKThis 3rd edition provides an insight into the mathematical crossroads formed by functional analysis (the macroscopic approach), partial differential equations (the mesoscopic approach) and probability (the microscopic approach) via the mathematics needed for the hard parts of Markov processes. It brings these three fields of analysis together, providing a comprehensive study of Markov processes from a broad perspective. The material is carefully and effectively explained, resulting in a surprisingly readable account of the subject. The main focus is on a powerful method for future research in elliptic boundary value problems and Markov processes via semigroups, the Boutet de Monvel calculus. A broad spectrum of readers will easily appreciate the stochastic intuition that this edition conveys. In fact, the book will provide a solid foundation for both researchers and graduate students in pure and applied mathematics interested in functional analysis, partial differential equations, Markov processes and the theory of pseudo-differential operators, a modern version of the classical potential theory.
Real Analysis (Classic Version)
Author: Halsey Royden
Publisher: Pearson Modern Classics for Advanced Mathematics Series
Published: 2017-02-13
Total Pages: 0
ISBN-13: 9780134689494
DOWNLOAD EBOOKThis text is designed for graduate-level courses in real analysis. Real Analysis, 4th Edition, covers the basic material that every graduate student should know in the classical theory of functions of a real variable, measure and integration theory, and some of the more important and elementary topics in general topology and normed linear space theory. This text assumes a general background in undergraduate mathematics and familiarity with the material covered in an undergraduate course on the fundamental concepts of analysis.
Markov Chains and Stochastic Stability
Author: Sean Meyn
Publisher: Cambridge University Press
Published: 2009-04-02
Total Pages: 623
ISBN-13: 0521731828
DOWNLOAD EBOOKNew up-to-date edition of this influential classic on Markov chains in general state spaces. Proofs are rigorous and concise, the range of applications is broad and knowledgeable, and key ideas are accessible to practitioners with limited mathematical background. New commentary by Sean Meyn, including updated references, reflects developments since 1996.
Image Analysis, Random Fields and Markov Chain Monte Carlo Methods
Author: Gerhard Winkler
Publisher: Springer Science & Business Media
Published: 2012-12-06
Total Pages: 389
ISBN-13: 3642557600
DOWNLOAD EBOOK"This book is concerned with a probabilistic approach for image analysis, mostly from the Bayesian point of view, and the important Markov chain Monte Carlo methods commonly used....This book will be useful, especially to researchers with a strong background in probability and an interest in image analysis. The author has presented the theory with rigor...he doesn’t neglect applications, providing numerous examples of applications to illustrate the theory." -- MATHEMATICAL REVIEWS
Markov Processes, Semigroups, and Generators
Author: Vassili N. Kolokoltsov
Publisher: Walter de Gruyter
Published: 2011
Total Pages: 449
ISBN-13: 3110250101
DOWNLOAD EBOOKThis 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
Ergodic Behavior of Markov Processes
Author: Alexei Kulik
Publisher: Walter de Gruyter GmbH & Co KG
Published: 2017-11-20
Total Pages: 316
ISBN-13: 3110458713
DOWNLOAD EBOOKThe general topic of this book is the ergodic behavior of Markov processes. A detailed introduction to methods for proving ergodicity and upper bounds for ergodic rates is presented in the first part of the book, with the focus put on weak ergodic rates, typical for Markov systems with complicated structure. The second part is devoted to the application of these methods to limit theorems for functionals of Markov processes. The book is aimed at a wide audience with a background in probability and measure theory. Some knowledge of stochastic processes and stochastic differential equations helps in a deeper understanding of specific examples. Contents Part I: Ergodic Rates for Markov Chains and Processes Markov Chains with Discrete State Spaces General Markov Chains: Ergodicity in Total Variation MarkovProcesseswithContinuousTime Weak Ergodic Rates Part II: Limit Theorems The Law of Large Numbers and the Central Limit Theorem Functional Limit Theorems
Functional Analysis in Markov Processes
Author: M. Fukushima
Publisher: Springer
Published: 2006-11-14
Total Pages: 316
ISBN-13: 354039155X
DOWNLOAD EBOOKIntroduction to Ergodic rates for Markov chains and processes
Author: Kulik, Alexei
Publisher: Universitätsverlag Potsdam
Published: 2015-10-20
Total Pages: 138
ISBN-13: 3869563389
DOWNLOAD EBOOKThe present lecture notes aim for an introduction to the ergodic behaviour of Markov Processes and addresses graduate students, post-graduate students and interested readers. Different tools and methods for the study of upper bounds on uniform and weak ergodic rates of Markov Processes are introduced. These techniques are then applied to study limit theorems for functionals of Markov processes. This lecture course originates in two mini courses held at University of Potsdam, Technical University of Berlin and Humboldt University in spring 2013 and Ritsumameikan University in summer 2013. Alexei Kulik, Doctor of Sciences, is a Leading researcher at the Institute of Mathematics of Ukrainian National Academy of Sciences.
