Markov Processes And Potential Theory

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Language : en
Publisher by : Academic Press
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Description : Markov Processes and Potential Theory


Markov Processes And Potential Theory

Author by : Robert McCallum Blumenthal
Language : en
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Markov Processes And Potential Theory

Author by : Mathematics Research Center (United States. Army)
Language : en
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Pseudo Differential Operators Markov Processes Markov Processes And Applications

Author by : Niels Jacob
Language : en
Publisher by : Imperial College Press
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Description : This work covers two topics in detail: Fourier analysis, with emphasis on positivity and also on some function spaces and multiplier theorems; and one-parameter operator semigroups with emphasis on Feller semigroups and Lp-sub-Markovian semigroups. In addition, Dirichlet forms are treated.


Markov Processes And Potential Theory

Author by : Joshua Chover
Language : en
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Markov Processes

Author by : Evgenij Borisovic Dynkin
Language : en
Publisher by : Springer Science & Business Media
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Description : The modem theory of Markov processes has its origins in the studies of A. A. MARKOV (1906-1907) on sequences of experiments "connected in a chain" and in the attempts to describe mathematically the physical phenomenon known as Brownian motion (L. BACHELlER 1900, A. EIN STEIN 1905). The first correct mathematical construction of a Markov process with continuous trajectories was given by N. WIENER in 1923. (This process is often called the Wiener process.) The general theory of Markov processes was developed in the 1930's and 1940's by A. N. KOL MOGOROV, W. FELLER, W. DOEBLlN, P. LEVY, J. L. DOOB, and others. During the past ten years the theory of Markov processes has entered a new period of intensive development. The methods of the theory of semigroups of linear operators made possible further progress in the classification of Markov processes by their infinitesimal characteristics. The broad classes of Markov processes with continuous trajectories be came the main object of study. The connections between Markov pro cesses and classical analysis were further developed. It has become possible not only to apply the results and methods of analysis to the problems of probability theory, but also to investigate analytic problems using probabilistic methods. Remarkable new connections between Markov processes and potential theory were revealed. The foundations of the theory were reviewed critically: the new concept of strong Markov process acquired for the whole theory of Markov processes great importance.


Chance Choice

Author by : Kai Lai Chung
Language : en
Publisher by : World Scientific
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Description : This book begins with a historical essay entitled OC Will the Sun Rise Again?OCO and ends with a general address entitled OC Mathematics and ApplicationsOCO. The articles cover an interesting range of topics: combinatoric probabilities, classical limit theorems, Markov chains and processes, potential theory, Brownian motion, SchrAdingerOCoFeynman problems, etc. They include many addresses presented at international conferences and special seminars, as well as memorials to and reminiscences of prominent contemporary mathematicians and reviews of their works. Rare old photos of many of them enliven the book. Contents: On Mutually Favorable Events; On Fluctuations in Coin-Tossing; On a Stochastic Approximation Method; On the Martin Boundary for Markov Chains; A Cluster of Great Formulas; Probabilistic Methods in Markov Chains; Markov Processes with Infinities; Probability Methods in Potential Theory; Plya''s Work in Probability; Probability and Doob; In Memory of L(r)vy and Fr(r)chet; and other papers. Readership: Graduate students, teachers and researchers in probability and statistics."


General Theory Of Markov Processes

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Language : en
Publisher by : Academic Press
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Description : General Theory of Markov Processes


Continuous Time Markov Processes

Author by : Thomas Milton Liggett
Language : en
Publisher by : American Mathematical Soc.
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Description : Markov processes are among the most important stochastic processes for both theory and applications. This book develops the general theory of these processes, and applies this theory to various special examples. The initial chapter is devoted to the most important classical example - one dimensional Brownian motion. This, together with a chapter on continuous time Markov chains, provides the motivation for the general setup based on semigroups and generators. Chapters on stochastic calculus and probabilistic potential theory give an introduction to some of the key areas of application of Brownian motion and its relatives. A chapter on interacting particle systems treats a more recently developed class of Markov processes that have as their origin problems in physics and biology. This is a textbook for a graduate course that can follow one that covers basic probabilistic limit theorems and discrete time processes.