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Markov Processes and Potential Theory

This advanced text explores the relationship between Markov processes and potential theory, in addition to aspects of the theory;

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Asymptotic Properties of Permanental Sequences

sequences related to birth and death processes and autoregressive Gaussian sequences using techniques from the theory of Gaussian processes and;

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Symmetric Markov Processes, Time Change, and Boundary Theory (LMS-35)

theory of symmetric Markov processes, including recurrence/transience criteria, probabilistic potential theory, additive functional theory, and;

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Potential Theory

M. Brelot: Historical introduction.- H. Bauer: Harmonic spaces and associated Markov processes.- J.M. Bony: Operateurs elliptiques;

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Boundary Value Problems and Markov Processes: Functional Analysis Methods for Markov Processes

, Markov processes and the theory of pseudo-differential operators, a modern version of the classical potential theory.;

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Semi-Dirichlet Forms and Markov Processes

and powerful tools in the theory of Markov processes and their applications. The theory is well studied and used in various fields. In this;

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Pseudo Differential Operators And Markov Processes, Volume Iii

considerations. The potential theory of these processes is further developed and applications are discussed. Due to the non-locality of the generators;

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Dirichlet Forms and Symmetric Markov Processes

is unified with the probabilistic potential theory based on symmetric Markov processes and developed further in conjunction with the stochastic;

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Generated Dynamics of Markov and Quantum Processes

This book presents Markov and quantum processes as two sides of a coin called generated stochastic processes. It deals with quantum;

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An Introduction to Markov Processes

Provides a more accessible introduction than other books on Markov processes by emphasizing the structure of the subject and avoiding;

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Finite Markov Processes and Their Applications

A self-contained treatment of finite Markov chains and processes, this text covers both theory and applications. Author Marius Iosifescu;

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Hidden Markov Processes

, such as ergodicity of Markov processes, Markov Chain Monte Carlo (MCMC), information theory, and large deviation theory for both i.i.d and;

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General Irreducible Markov Chains and Non-Negative Operators

The purpose of this book is to present the theory of general irreducible Markov chains and to point out the connection between this and the;

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Semi-Markov Processes

Semi-Markov Processes: Applications in System Reliability and Maintenance is a modern view of discrete state space and continuous time;

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Multidimensional Diffusion Processes

From the reviews: This book is an excellent presentation of the application of martingale theory to the theory of Markov processes;

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Markov Processes and Applications

This well-written book provides a clear and accessible treatment of the theory of discrete and continuous-time Markov chains, with an;

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Labelled Markov Processes

Labelled Markov processes are probabilistic versions of labelled transition systems with continuous state spaces. The book covers basic;

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Markov Processes, Gaussian Processes, and Local Times

entrance for students and for experts in related fields. The book starts by developing the fundamentals of Markov process theory and then;

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Ergodic Behavior of Markov Processes

The general topic of this book is the ergodic behavior of Markov processes. A detailed introduction to methods for proving ergodicity and;

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First Look At Stochastic Processes, A

times, branching processes, stock option pricing, and Markov Chain Monte Carlo (MCMC) algorithms.The focus is always on making the theory as;

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First Look At Stochastic Processes, A

times, branching processes, stock option pricing, and Markov Chain Monte Carlo (MCMC) algorithms.The focus is always on making the theory as;

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Markov Processes, Gaussian Processes, and Local Times

be applied to obtain new properties of Markov processes by using well-established techniques in Gaussian process theory. This original;

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Controlled Markov Processes and Viscosity Solutions

This book is intended as an introduction to optimal stochastic control for continuous time Markov processes and to the theory of viscosity;

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Elements Of Stochastic Modelling

of probability theory and then covers the following topics: Markov chains, Markov decision processes, jump Markov processes, elements of queueing theory;

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Studies in the Theory of Random Processes

limit theorems for Markov processes. Specialists, researchers, and students in the field of probability will find it a source of important;

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Markov Chains

with some background in basic probability theory, focuses on Markov chains and quickly develops a coherent and rigorous theory whilst showing;

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London Mathematical Society Lecture Note Series

The theory of Markov Processes has become a powerful tool in partial differential equations and potential theory with important;

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