Introduction To The Theory Of Random Processes

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Introduction to the Theory of Random Processes

Author : Iosif Il?ich Gikhman,Anatoli? Vladimirovich Skorokhod
Publisher : Courier Corporation
Page : 537 pages
File Size : 44,8 Mb
Release : 1996-01-01
Category : Mathematics
ISBN : 9780486693873

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Introduction to the Theory of Random Processes by Iosif Il?ich Gikhman,Anatoli? Vladimirovich Skorokhod Pdf

Rigorous exposition suitable for elementary instruction. Covers measure theory, axiomatization of probability theory, processes with independent increments, Markov processes and limit theorems for random processes, more. A wealth of results, ideas, and techniques distinguish this text. Introduction. Bibliography. 1969 edition.

Introduction to the Theory of Random Processes

Author : Nikolaĭ Vladimirovich Krylov
Publisher : American Mathematical Soc.
Page : 245 pages
File Size : 51,9 Mb
Release : 2002
Category : Stochastic processes
ISBN : 9780821829851

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Introduction to the Theory of Random Processes by Nikolaĭ Vladimirovich Krylov Pdf

This book concentrates on some general facts and ideas of the theory of stochastic processes. The topics include the Wiener process, stationary processes, infinitely divisible processes, and Ito stochastic equations. Basics of discrete time martingales are also presented and then used in one way or another throughout the book. Another common feature of the main body of the book is using stochastic integration with respect to random orthogonal measures. In particular, it is used forspectral representation of trajectories of stationary processes and for proving that Gaussian stationary processes with rational spectral densities are components of solutions to stochastic equations. In the case of infinitely divisible processes, stochastic integration allows for obtaining arepresentation of trajectories through jump measures. The Ito stochastic integral is also introduced as a particular case of stochastic integrals with respect to random orthogonal measures. Although it is not possible to cover even a noticeable portion of the topics listed above in a short book, it is hoped that after having followed the material presented here, the reader will have acquired a good understanding of what kind of results are available and what kind of techniques are used toobtain them. With more than 100 problems included, the book can serve as a text for an introductory course on stochastic processes or for independent study. Other works by this author published by the AMS include, Lectures on Elliptic and Parabolic Equations in Holder Spaces and Introduction to the Theoryof Diffusion Processes.

Introduction to the Theory of Random Processes

Author : I. I. Gikhman,A. V. Skorokhod
Publisher : Unknown
Page : 516 pages
File Size : 55,7 Mb
Release : 1996
Category : Electronic
ISBN : OCLC:638920102

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Introduction to the Theory of Random Processes by I. I. Gikhman,A. V. Skorokhod Pdf

An Introduction to the Theory of Point Processes

Author : D.J. Daley,D. Vere-Jones
Publisher : Springer Science & Business Media
Page : 471 pages
File Size : 52,6 Mb
Release : 2006-04-10
Category : Mathematics
ISBN : 9780387215648

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An Introduction to the Theory of Point Processes by D.J. Daley,D. Vere-Jones Pdf

Point processes and random measures find wide applicability in telecommunications, earthquakes, image analysis, spatial point patterns, and stereology, to name but a few areas. The authors have made a major reshaping of their work in their first edition of 1988 and now present their Introduction to the Theory of Point Processes in two volumes with sub-titles Elementary Theory and Models and General Theory and Structure. Volume One contains the introductory chapters from the first edition, together with an informal treatment of some of the later material intended to make it more accessible to readers primarily interested in models and applications. The main new material in this volume relates to marked point processes and to processes evolving in time, where the conditional intensity methodology provides a basis for model building, inference, and prediction. There are abundant examples whose purpose is both didactic and to illustrate further applications of the ideas and models that are the main substance of the text.

Introduction to the Theory of Random Processes

Author : Iosif Ilitch Gikhman,Anatoli Vladimirovitch Skorokhod
Publisher : Unknown
Page : 516 pages
File Size : 42,6 Mb
Release : 1965
Category : Electronic
ISBN : OCLC:638920102

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Introduction to the Theory of Random Processes by Iosif Ilitch Gikhman,Anatoli Vladimirovitch Skorokhod Pdf

An Introduction to Continuous-Time Stochastic Processes

Author : Vincenzo Capasso,David Bakstein
Publisher : Springer Science & Business Media
Page : 348 pages
File Size : 46,6 Mb
Release : 2008-01-03
Category : Mathematics
ISBN : 9780817644284

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An Introduction to Continuous-Time Stochastic Processes by Vincenzo Capasso,David Bakstein Pdf

This concisely written book is a rigorous and self-contained introduction to the theory of continuous-time stochastic processes. Balancing theory and applications, the authors use stochastic methods and concrete examples to model real-world problems from engineering, biomathematics, biotechnology, and finance. Suitable as a textbook for graduate or advanced undergraduate courses, the work may also be used for self-study or as a reference. The book will be of interest to students, pure and applied mathematicians, and researchers or practitioners in mathematical finance, biomathematics, physics, and engineering.

Theory of Probability and Random Processes

Author : Leonid Koralov,Yakov G. Sinai
Publisher : Springer Science & Business Media
Page : 346 pages
File Size : 55,9 Mb
Release : 2007-08-10
Category : Mathematics
ISBN : 9783540688297

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Theory of Probability and Random Processes by Leonid Koralov,Yakov G. Sinai Pdf

A one-year course in probability theory and the theory of random processes, taught at Princeton University to undergraduate and graduate students, forms the core of this book. It provides a comprehensive and self-contained exposition of classical probability theory and the theory of random processes. The book includes detailed discussion of Lebesgue integration, Markov chains, random walks, laws of large numbers, limit theorems, and their relation to Renormalization Group theory. It also includes the theory of stationary random processes, martingales, generalized random processes, and Brownian motion.

An Introduction to Stochastic Processes and Their Applications

Author : Petar Todorovic
Publisher : Springer Science & Business Media
Page : 302 pages
File Size : 49,6 Mb
Release : 2012-12-06
Category : Mathematics
ISBN : 9781461397427

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An Introduction to Stochastic Processes and Their Applications by Petar Todorovic Pdf

This text on stochastic processes and their applications is based on a set of lectures given during the past several years at the University of California, Santa Barbara (UCSB). It is an introductory graduate course designed for classroom purposes. Its objective is to provide graduate students of statistics with an overview of some basic methods and techniques in the theory of stochastic processes. The only prerequisites are some rudiments of measure and integration theory and an intermediate course in probability theory. There are more than 50 examples and applications and 243 problems and complements which appear at the end of each chapter. The book consists of 10 chapters. Basic concepts and definitions are pro vided in Chapter 1. This chapter also contains a number of motivating ex amples and applications illustrating the practical use of the concepts. The last five sections are devoted to topics such as separability, continuity, and measurability of random processes, which are discussed in some detail. The concept of a simple point process on R+ is introduced in Chapter 2. Using the coupling inequality and Le Cam's lemma, it is shown that if its counting function is stochastically continuous and has independent increments, the point process is Poisson. When the counting function is Markovian, the sequence of arrival times is also a Markov process. Some related topics such as independent thinning and marked point processes are also discussed. In the final section, an application of these results to flood modeling is presented.

Introduction to the Theory of Random Processes

Author : Nikolaĭ Vladimirovich Krylov
Publisher : Unknown
Page : 230 pages
File Size : 55,7 Mb
Release : 2002
Category : Stochastic processes
ISBN : 1470420945

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Introduction to the Theory of Random Processes by Nikolaĭ Vladimirovich Krylov Pdf

This work concentrates on some general facts and ideas of the theory of stochastic processes. The topics include the Wiener process, stationary processes, infinitely divisible processes, and Ito stochastic equations. Basics of discrete time martingales are also presented and then used in one way or another throughout the book.

Random Processes

Author : M. Rosenblatt
Publisher : Springer Science & Business Media
Page : 236 pages
File Size : 48,8 Mb
Release : 2012-12-06
Category : Mathematics
ISBN : 9781461298526

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Random Processes by M. Rosenblatt Pdf

This text has as its object an introduction to elements of the theory of random processes. Strictly speaking, only a good background in the topics usually associated with a course in Advanced Calculus (see, for example, the text of Apostol [1]) and the elements of matrix algebra is required although additional background is always helpful. N onethe less a strong effort has been made to keep the required background on the level specified above. This means that a course based on this book would be appropriate for a beginning graduate student or an advanced undergraduate. Previous knowledge of probability theory is not required since the discussion starts with the basic notions of probability theory. Chapters II and III are concerned with discrete probability spaces and elements of the theory of Markov chains respectively. These two chapters thus deal with probability theory for finite or countable models. The object is to present some of the basic ideas and problems of the theory in a discrete context where difficulties of heavy technique and detailed measure theoretic discussions do not obscure the ideas and problems.

Introduction To Stochastic Processes

Author : Mu-fa Chen,Yong-hua Mao
Publisher : World Scientific
Page : 245 pages
File Size : 51,7 Mb
Release : 2021-05-25
Category : Mathematics
ISBN : 9789814740326

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Introduction To Stochastic Processes by Mu-fa Chen,Yong-hua Mao Pdf

The objective of this book is to introduce the elements of stochastic processes in a rather concise manner where we present the two most important parts — Markov chains and stochastic analysis. The readers are led directly to the core of the main topics to be treated in the context. Further details and additional materials are left to a section containing abundant exercises for further reading and studying.In the part on Markov chains, the focus is on the ergodicity. By using the minimal nonnegative solution method, we deal with the recurrence and various types of ergodicity. This is done step by step, from finite state spaces to denumerable state spaces, and from discrete time to continuous time. The methods of proofs adopt modern techniques, such as coupling and duality methods. Some very new results are included, such as the estimate of the spectral gap. The structure and proofs in the first part are rather different from other existing textbooks on Markov chains.In the part on stochastic analysis, we cover the martingale theory and Brownian motions, the stochastic integral and stochastic differential equations with emphasis on one dimension, and the multidimensional stochastic integral and stochastic equation based on semimartingales. We introduce three important topics here: the Feynman-Kac formula, random time transform and Girsanov transform. As an essential application of the probability theory in classical mathematics, we also deal with the famous Brunn-Minkowski inequality in convex geometry.This book also features modern probability theory that is used in different fields, such as MCMC, or even deterministic areas: convex geometry and number theory. It provides a new and direct routine for students going through the classical Markov chains to the modern stochastic analysis.

Introduction to Random Processes

Author : Yurii A. Rozanov
Publisher : Springer Science & Business Media
Page : 127 pages
File Size : 54,6 Mb
Release : 2012-12-06
Category : Mathematics
ISBN : 9783642727177

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Introduction to Random Processes by Yurii A. Rozanov Pdf

Today, the theory of random processes represents a large field of mathematics with many different branches, and the task of choosing topics for a brief introduction to this theory is far from being simple. This introduction to the theory of random processes uses mathematical models that are simple, but have some importance for applications. We consider different processes, whose development in time depends on some random factors. The fundamental problem can be briefly circumscribed in the following way: given some relatively simple characteristics of a process, compute the probability of another event which may be very complicated; or estimate a random variable which is related to the behaviour of the process. The models that we consider are chosen in such a way that it is possible to discuss the different methods of the theory of random processes by referring to these models. The book starts with a treatment of homogeneous Markov processes with a countable number of states. The main topic is the ergodic theorem, the method of Kolmogorov's differential equations (Secs. 1-4) and the Brownian motion process, the connecting link being the transition from Kolmogorov's differential-difference equations for random walk to a limit diffusion equation (Sec. 5).

Probability, Random Processes, and Ergodic Properties

Author : Robert M. Gray
Publisher : Springer Science & Business Media
Page : 309 pages
File Size : 40,6 Mb
Release : 2013-04-18
Category : Mathematics
ISBN : 9781475720242

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Probability, Random Processes, and Ergodic Properties by Robert M. Gray Pdf

This book has been written for several reasons, not all of which are academic. This material was for many years the first half of a book in progress on information and ergodic theory. The intent was and is to provide a reasonably self-contained advanced treatment of measure theory, prob ability theory, and the theory of discrete time random processes with an emphasis on general alphabets and on ergodic and stationary properties of random processes that might be neither ergodic nor stationary. The intended audience was mathematically inc1ined engineering graduate students and visiting scholars who had not had formal courses in measure theoretic probability . Much of the material is familiar stuff for mathematicians, but many of the topics and results have not previously appeared in books. The original project grew too large and the first part contained much that would likely bore mathematicians and dis courage them from the second part. Hence I finally followed the suggestion to separate the material and split the project in two. The original justification for the present manuscript was the pragmatic one that it would be a shame to waste all the effort thus far expended. A more idealistic motivation was that the presentation bad merit as filling a unique, albeit smaIl, hole in the literature.

A First Look At Stochastic Processes

Author : Jeffrey S Rosenthal
Publisher : World Scientific
Page : 213 pages
File Size : 51,9 Mb
Release : 2019-09-26
Category : Mathematics
ISBN : 9789811207921

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A First Look At Stochastic Processes by Jeffrey S Rosenthal Pdf

This textbook introduces the theory of stochastic processes, that is, randomness which proceeds in time. Using concrete examples like repeated gambling and jumping frogs, it presents fundamental mathematical results through simple, clear, logical theorems and examples. It covers in detail such essential material as Markov chain recurrence criteria, the Markov chain convergence theorem, and optional stopping theorems for martingales. The final chapter provides a brief introduction to Brownian motion, Markov processes in continuous time and space, Poisson processes, and renewal theory.Interspersed throughout are applications to such topics as gambler's ruin probabilities, random walks on graphs, sequence waiting times, branching processes, stock option pricing, and Markov Chain Monte Carlo (MCMC) algorithms.The focus is always on making the theory as well-motivated and accessible as possible, to allow students and readers to learn this fascinating subject as easily and painlessly as possible.