Author: Lorenzo Finesso
Publisher:
ISBN:
Category :
Languages : en
Pages : 56

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Author: K. L. Chung
Publisher:
ISBN:
Category : Equations
Languages : en
Pages : 80

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Author: Olle Häggström
Publisher: Cambridge University Press
ISBN: 9780521890014
Category : Mathematics
Languages : en
Pages : 132

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Book Description
Based on a lecture course given at Chalmers University of Technology, this 2002 book is ideal for advanced undergraduate or beginning graduate students. The author first develops the necessary background in probability theory and Markov chains before applying it to study a range of randomized algorithms with important applications in optimization and other problems in computing. Amongst the algorithms covered are the Markov chain Monte Carlo method, simulated annealing, and the recent Propp-Wilson algorithm. This book will appeal not only to mathematicians, but also to students of statistics and computer science. The subject matter is introduced in a clear and concise fashion and the numerous exercises included will help students to deepen their understanding.

Author: Donald Austin
Publisher:
ISBN:
Category : Equations
Languages : en
Pages : 32

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Book Description
We investigate analytic properties of non-negative matrices satisfying probabilistically motivated functional relations which are weaker than the semi-group condition. The fundamental differentiation theorem for transition functions of a Markov process is proved in the abstract space case.

Author: Edgar J. Gilbert
Publisher:
ISBN:
Category : Markov processes
Languages : en
Pages : 16

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Book Description

Author: John G. Kemeny
Publisher:
ISBN:
Category : Markov processes
Languages : en
Pages : 226

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Book Description

Author: George Yin
Publisher: Springer Science & Business Media
ISBN: 9780387219486
Category : Business & Economics
Languages : en
Pages : 372

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Book Description
Focusing on discrete-time-scale Markov chains, the contents of this book are an outgrowth of some of the authors' recent research. The motivation stems from existing and emerging applications in optimization and control of complex hybrid Markovian systems in manufacturing, wireless communication, and financial engineering. Much effort in this book is devoted to designing system models arising from these applications, analyzing them via analytic and probabilistic techniques, and developing feasible computational algorithms so as to reduce the inherent complexity. This book presents results including asymptotic expansions of probability vectors, structural properties of occupation measures, exponential bounds, aggregation and decomposition and associated limit processes, and interface of discrete-time and continuous-time systems. One of the salient features is that it contains a diverse range of applications on filtering, estimation, control, optimization, and Markov decision processes, and financial engineering. This book will be an important reference for researchers in the areas of applied probability, control theory, operations research, as well as for practitioners who use optimization techniques. Part of the book can also be used in a graduate course of applied probability, stochastic processes, and applications.

Author: Marius Iosifescu
Publisher: Courier Corporation
ISBN: 0486150585
Category : Mathematics
Languages : en
Pages : 305

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Book Description
A self-contained treatment of finite Markov chains and processes, this text covers both theory and applications. Author Marius Iosifescu, vice president of the Romanian Academy and director of its Center for Mathematical Statistics, begins with a review of relevant aspects of probability theory and linear algebra. Experienced readers may start with the second chapter, a treatment of fundamental concepts of homogeneous finite Markov chain theory that offers examples of applicable models. The text advances to studies of two basic types of homogeneous finite Markov chains: absorbing and ergodic chains. A complete study of the general properties of homogeneous chains follows. Succeeding chapters examine the fundamental role of homogeneous infinite Markov chains in mathematical modeling employed in the fields of psychology and genetics; the basics of nonhomogeneous finite Markov chain theory; and a study of Markovian dependence in continuous time, which constitutes an elementary introduction to the study of continuous parameter stochastic processes.

Author: David Freedman
Publisher: Springer Science & Business Media
ISBN: 1461255007
Category : Mathematics
Languages : en
Pages : 395

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Book Description
A long time ago I started writing a book about Markov chains, Brownian motion, and diffusion. I soon had two hundred pages of manuscript and my publisher was enthusiastic. Some years and several drafts later, I had a thousand pages of manuscript, and my publisher was less enthusiastic. So we made it a trilogy: Markov Chains Brownian Motion and Diffusion Approximating Countable Markov Chains familiarly - MC, B & D, and ACM. I wrote the first two books for beginning graduate students with some knowledge of probability; if you can follow Sections 10.4 to 10.9 of Markov Chains you're in. The first two books are quite independent of one another, and completely independent of the third. This last book is a monograph which explains one way to think about chains with instantaneous states. The results in it are supposed to be new, except where there are specific disclaim ers; it's written in the framework of Markov Chains. Most of the proofs in the trilogy are new, and I tried hard to make them explicit. The old ones were often elegant, but I seldom saw what made them go. With my own, I can sometimes show you why things work. And, as I will VB1 PREFACE argue in a minute, my demonstrations are easier technically. If I wrote them down well enough, you may come to agree.

Author:
Publisher:
ISBN:
Category : Weights and measures
Languages : en
Pages : 574

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Book Description