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An Introduction to Markov Processes, Stroock Daniel W.


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Автор: Stroock Daniel W.
Название:  An Introduction to Markov Processes   (Даниэль Струк: Введение в цепи Маркова)
Издательство: Springer
Классификация:
Вероятность и статистика
Прикладная математика

ISBN: 3540234519
ISBN-13(EAN): 9783540234517
ISBN: 3-540-23451-9
ISBN-13(EAN): 978-3-540-23451-7
Обложка/Формат: Paperback
Страницы: 171
Вес: 0.304 кг.
Дата издания: 2005
Серия: Graduate Texts in Mathematics
Язык: ENG
Размер: 23.72 x 15.49 x 1.14 cm
Читательская аудитория: Postgraduate, research & scholarly
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: This book provides a rigorous but elementary introduction to the theory of Markov Processes on a countable state space. It should be accessible to students with a solid undergraduate background in mathematics, including students from engineering, economics, physics, and biology. Topics covered are: Doeblins theory, general ergodic properties, and continuous time processes. A whole chapter is devoted to reversible processes and the use of their associated Dirichlet forms to estimate the rate of convergence to equilibrium.
Дополнительное описание: Формат: 235x155
Круг читателей: Advanced undergraduates with strong mathematics preparation and graduate students looking for a non-measure-theoretic, but rigorous, introduction to Markov processes
Ключевые слова: Markov chains
ergodic theory
reversible Markov chains
Язык: eng
Оглавление: Random Walks a Good Place to Begin.- Doeblin's Theory for Markov Chains.- More about the Ergodic Theory of Markov Chains.- Markov Processes in Continuous Time.- Reversible Markov Processes.- Some Mild Measure Theory.- Notation.- References.- Index.





Discrete-Time Markov Control Processes

Автор: Hernandez-Lerma
Название: Discrete-Time Markov Control Processes
ISBN: 0387945792 ISBN-13(EAN): 9780387945798
Издательство: Springer
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Цена: 11215 р.
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Описание: This text provides a unified treatment of some recent theoretical developments on Markov control processes. Interest is mainly confined to MCPs with Borel state and control spaces, and possibly unbound costs and non-compact control constraint sets.

Controlled Markov Processes and Viscosity Solutions

Автор: Fleming Wendell H., Soner H.M.
Название: Controlled Markov Processes and Viscosity Solutions
ISBN: 0387260455 ISBN-13(EAN): 9780387260457
Издательство: Springer
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Цена: 11219 р.
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Описание: This book is intended as an introduction to optimal stochastic control for continuous time Markov processes and to the theory of viscosity solutions. The authors approach stochastic control problems by the method of dynamic programming. The text provides an introduction to dynamic programming for deterministic optimal control problems, as well as to the corresponding theory of viscosity solutions. A new Chapter X gives an introduction to the role of stochastic optimal control in portfolio optimization and in pricing derivatives in incomplete markets. Chapter VI of the First Edition has been completely rewritten, to emphasize the relationships between logarithmic transformations and risk sensitivity. A new Chapter XI gives a concise introduction to two-controller, zero-sum differential games. Also covered are controlled Markov diffusions and viscosity solutions of Hamilton-Jacobi-Bellman equations. The authors have tried, through illustrative examples and selective material, to connect stochastic control theory with other mathematical areas (e.g. large deviations theory) and with applications to engineering, physics, management, and finance. In this Second Edition, new material on applications to mathematical finance has been added. Concise introductions to risk-sensitive control theory, nonlinear H-infinity control and differential games are also included.

Handbook of Markov Decision Processes / Methods and Applications

Автор: Feinberg Eugene A., Shwartz Adam
Название: Handbook of Markov Decision Processes / Methods and Applications
ISBN: 0792374592 ISBN-13(EAN): 9780792374596
Издательство: Springer
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Цена: 27957 р.
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Описание: The theory of Markov Decision Processes - also known under several other names including sequential stochastic optimization, discrete-time stochastic control, and stochastic dynamic programming - studies sequential optimization of discrete time stochastic systems. Fundamentally, this is a methodology that examines and analyzes a discrete-time stochastic system whose transition mechanism can be controlled over time. Each control policy defines the stochastic process and values of objective functions associated with this process. Its objective is to select a "good" control policy. In real life, decisions that humans and computers make on all levels usually have two types of impacts: (i) they cost or save time, money, or other resources, or they bring revenues, as well as (ii) they have an impact on the future, by influencing the dynamics. In many situations, decisions with the largest immediate profit may not be good in view of future events. Markov Decision Processes (MDPs) model this paradigm and provide results on the structure and existence of good policies and on methods for their calculations. MDPs are attractive to many researchers because they are important both from the practical and the intellectual points of view. MDPs provide tools for the solution of important real-life problems. In particular, many business and engineering applications use MDP models. Analysis of various problems arising in MDPs leads to a large variety of interesting mathematical and computational problems. Accordingly, the Handbook of Markov Decision Processes is split into three parts: Part I deals with models with finite state and action spaces and Part II deals with infinite state problems, and Part III examines specific applications. Individual chapters are written by leading experts on the subject.

From Markov Jump Processes to Spatial Queues

Автор: Breuer L.
Название: From Markov Jump Processes to Spatial Queues
ISBN: 1402011040 ISBN-13(EAN): 9781402011047
Издательство: Springer
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Цена: 9817 р.
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Описание: From Markov Jump Processes to Spatial Queues aims to develop a unified theory of spatial queues that yields concrete results for the performance analysis of mobile communication networks. A particular objective is to develop the most natural generalization of existing concepts (e.g. the BMAP) toward the needs of mobile communication networks. To these belong the spatial distribution of batch arrivals and users in the system as well as time-inhomogeneous (e.g. periodic) arrival intensities and user movements. One of the major recent challenges for the stochastic modelling of communication systems is the emergence of wireless networks, which are used by more and more subscribers today. The main new feature of those, which is not covered by classical queuing theory, clearly is the importance of the user location within the area that is served by the base stations of the network. In the framework of queuing theory, this opens up the natural extension of classical queuing models towards queues with a structured space in which users are served. The present book is intended to introduce this extension under the name of spatial queues. The main point of view and the general approach will be that of Markov jump processes. We start with a closer look into the theory. Then we present new results for the theory of stochastic processes as well as for classical queuing theory. Finally we introduce the new concepts of spatial Markovian arrival processes and spatial queues. The main text is divided into three parts. The first part provides a new presentation of the theory of Markov jump processes. We derive a number of new results, especially for time-inhomogeneous processes, which have been neglected too much in the current textbooks on stochastic processes. For the first time, the class of Markov-additive jump processes is analysed in detail. This extends and unifies all Markovian arrival processes that have been proposed up to now (including arrivals for fluid queues) and provides a foundation for the subsequent introduction of spatial Markovian arrival processes.The second part contains new results for classical queues with BMAP input. These include the first explicit formulae for the distribution of periodic queues. The class of fluid Markovian arrival processes is introduced, and we give statistical estimates for the parameters of a BMAP. In the third part, the concepts of spatial Markovian arrival processes (abbreviated: SMAPs) and spatial queues are introduced. After that, periodic spatial Markovian queues are analysed as a model for the cells of a wireless communication network. From Markov Jump Processes to Spatial Queues is intended to reach queuing theorists, researchers in the field of communication systems, as well as engineers with some background in probability theory. Furthermore, it is suitable as a textbook for advanced queuing theory on the graduate or post-graduate level.

Cycle Representations of Markov Processes

Автор: Kalpazidou Sophia L.
Название: Cycle Representations of Markov Processes
ISBN: 0387291660 ISBN-13(EAN): 9780387291666
Издательство: Springer
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Цена: 15427 р.
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Описание: This book is a prototype providing new insight into Markovian dependence via the cycle decompositions. It presents a systematic account of a class of stochastic processes known as cycle (or circuit) processes - so-called because they may be defined by directed cycles. These processes have special and important properties through the interaction between the geometric properties of the trajectories and the algebraic characterization of the Markov process. An important application of this approach is the insight it provides to electrical networks and the duality principle of networks. In particular, it provides an entirely new approach to infinite electrical networks and their applications in topics as diverse as random walks, the classification of Riemann surfaces, and to operator theory.The second edition of this book adds new advances to many directions, which reveal wide-ranging interpretations of the cycle representations like homologic decompositions, orthogonality equations, Fourier series, semigroup equations, and disintegration of measures. The versatility of these interpretations is consequently motivated by the existence of algebraic-topological principles in the fundamentals of the cycle representations. This book contains chapter summaries as well as a number of detailed illustrations.Review of the earlier edition:"This is a very useful monograph which avoids ready ways and opens new research perspectives. It will certainly stimulate further work, especially on the interplay of algebraic and geometrical aspects of Markovian dependence and its generalizations."Math Reviews.

Further Topics on Discrete-Time Markov Control Processes

Автор: Hernandez-Lerma
Название: Further Topics on Discrete-Time Markov Control Processes
ISBN: 0387986944 ISBN-13(EAN): 9780387986944
Издательство: Springer
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Цена: 13089 р.
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Описание: Devotes to a systematic exposition of some developments in the theory of discrete-time Markov control processes.

Probability and statistics by example markov chains - a primer in random processes and their applications

Автор: Suhov, Yuri Kelbert, Mark
Название: Probability and statistics by example markov chains - a primer in random processes and their applications
ISBN: 0521612349 ISBN-13(EAN): 9780521612340
Издательство: Cambridge Academ
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Цена: 6556 р.
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Описание: Probability and Statistics are as much about intuition and problem solving as they are about theorem proving. Because of this, students can find it very difficult to make a successful transition from lectures to examinations to practice, since the problems involved can vary so much in nature. Since the subject is critical in many modern applications such as mathematical finance, quantitative management, telecommunications, signal processing, bioinformatics, as well as traditional ones such as insurance, social science andengineering, the authors have rectified deficiencies in traditional lecture-based methods by collecting together a wealth of exercises with complete solutions, adapted to needs and skills of students. Following on from the success of Probability and Statistics by Example: Basic Probability and Statistics, the authors here concentrate on random processes, particularly Markov processes, emphasising modelsrather than general constructions. Basic mathematical facts are supplied as and when they are needed andhistorical information is sprinkled throughout.

Measure-Valued Branching Markov Processes

Автор: Li
Название: Measure-Valued Branching Markov Processes
ISBN: 3642150039 ISBN-13(EAN): 9783642150036
Издательство: Springer
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Цена: 7479 р.
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Описание: Measure-valued branching processes arise as high density limits of branching particle systems. The Dawson-Watanabe superprocess is a special class of those. The author constructs superprocesses with Borel right underlying motions and general branching mechanisms and shows the existence of their Borel right realizations. He then uses transformations to derive the existence and regularity of several different forms of the superprocesses. This treatment simplifies the constructions and gives useful perspectives. Martingale problems of superprocesses are discussed under Feller type assumptions. The most important feature of the book is the systematic treatment of immigration superprocesses and generalized Ornstein--Uhlenbeck processes based on skew convolution semigroups. The volume addresses researchers in measure-valued processes, branching processes, stochastic analysis, biological and genetic models, and graduate students in probability theory and stochastic processes.

Markov chains and decision processes for engineers and managers

Название: Markov chains and decision processes for engineers and managers
ISBN: 1420051113 ISBN-13(EAN): 9781420051117
Издательство: Taylor&Francis
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Цена: 10135 р.
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Описание: Presents an introduction to finite Markov chains and Markov decision processes, with applications in engineering and management. This book introduces discrete-time, finite-state Markov chains, and Markov decision processes. It describes both algorithms and applications, enabling students to understand the logical basis for the algorithms.

Markov Processes,

Автор: Daniel T. Gillespie
Название: Markov Processes,
ISBN: 0122839552 ISBN-13(EAN): 9780122839559
Издательство: Elsevier Science
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Цена: 5138 р.
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Описание: Markov process theory is basically an extension of ordinary calculus to accommodate functions whose time evolutions are not entirely deterministic. This book develops the single-variable theory of both continuous and jump Markov processes. It is intended for physicists and chemists at the senior and graduate level.

Markov Processes for Stochastic Modeling,

Автор: Oliver Ibe
Название: Markov Processes for Stochastic Modeling,
ISBN: 0123744512 ISBN-13(EAN): 9780123744517
Издательство: Elsevier Science
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Цена: 6166 р.
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Описание: Markov processes are used to model systems with limited memory. This book discusses topics such as Markovian queuing system, continuous-time random walk, correlated random walk, Brownian motion, diffusion processes, hidden Markov models, Markov random fields, Markov point processes and Markov chain Monte Carlo.

Continuous-Time Markov Decision Processes

Автор: Guo
Название: Continuous-Time Markov Decision Processes
ISBN: 3642025463 ISBN-13(EAN): 9783642025464
Издательство: Springer
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Цена: 9349 р.
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Описание: Theory and Applications. .


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