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The Theory of Stochastic Processes I

The Theory of Stochastic Processes I
Author: Iosif I. Gikhman
Publisher: Springer
Total Pages: 587
Release: 2015-03-30
Genre: Mathematics
ISBN: 3642619436

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From the Reviews: "Gihman and Skorohod have done an excellent job of presenting the theory in its present state of rich imperfection." --D.W. Stroock, Bulletin of the American Mathematical Society, 1980


Stochastic Processes: General Theory

Stochastic Processes: General Theory
Author: Malempati M. Rao
Publisher: Springer Science & Business Media
Total Pages: 629
Release: 2013-03-14
Genre: Mathematics
ISBN: 1475765983

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Stochastic Processes: General Theory starts with the fundamental existence theorem of Kolmogorov, together with several of its extensions to stochastic processes. It treats the function theoretical aspects of processes and includes an extended account of martingales and their generalizations. Various compositions of (quasi- or semi-)martingales and their integrals are given. Here the Bochner boundedness principle plays a unifying role: a unique feature of the book. Applications to higher order stochastic differential equations and their special features are presented in detail. Stochastic processes in a manifold and multiparameter stochastic analysis are also discussed. Each of the seven chapters includes complements, exercises and extensive references: many avenues of research are suggested. The book is a completely revised and enlarged version of the author's Stochastic Processes and Integration (Noordhoff, 1979). The new title reflects the content and generality of the extensive amount of new material. Audience: Suitable as a text/reference for second year graduate classes and seminars. A knowledge of real analysis, including Lebesgue integration, is a prerequisite.


Theory and Applications of Stochastic Processes

Theory and Applications of Stochastic Processes
Author: Zeev Schuss
Publisher: Springer Science & Business Media
Total Pages: 486
Release: 2009-12-09
Genre: Mathematics
ISBN: 1441916059

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Stochastic processes and diffusion theory are the mathematical underpinnings of many scientific disciplines, including statistical physics, physical chemistry, molecular biophysics, communications theory and many more. Many books, reviews and research articles have been published on this topic, from the purely mathematical to the most practical. This book offers an analytical approach to stochastic processes that are most common in the physical and life sciences, as well as in optimal control and in the theory of filltering of signals from noisy measurements. Its aim is to make probability theory in function space readily accessible to scientists trained in the traditional methods of applied mathematics, such as integral, ordinary, and partial differential equations and asymptotic methods, rather than in probability and measure theory.


Probability Theory and Stochastic Processes

Probability Theory and Stochastic Processes
Author: Pierre Brémaud
Publisher: Springer Nature
Total Pages: 713
Release: 2020-04-07
Genre: Mathematics
ISBN: 3030401839

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The ultimate objective of this book is to present a panoramic view of the main stochastic processes which have an impact on applications, with complete proofs and exercises. Random processes play a central role in the applied sciences, including operations research, insurance, finance, biology, physics, computer and communications networks, and signal processing. In order to help the reader to reach a level of technical autonomy sufficient to understand the presented models, this book includes a reasonable dose of probability theory. On the other hand, the study of stochastic processes gives an opportunity to apply the main theoretical results of probability theory beyond classroom examples and in a non-trivial manner that makes this discipline look more attractive to the applications-oriented student. One can distinguish three parts of this book. The first four chapters are about probability theory, Chapters 5 to 8 concern random sequences, or discrete-time stochastic processes, and the rest of the book focuses on stochastic processes and point processes. There is sufficient modularity for the instructor or the self-teaching reader to design a course or a study program adapted to her/his specific needs. This book is in a large measure self-contained.


The Theory of Stochastic Processes

The Theory of Stochastic Processes
Author: D.R. Cox
Publisher: Routledge
Total Pages: 408
Release: 2017-09-04
Genre: Mathematics
ISBN: 135140895X

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This book should be of interest to undergraduate and postgraduate students of probability theory.


Stochastic Processes

Stochastic Processes
Author: Pierre Del Moral
Publisher: CRC Press
Total Pages: 866
Release: 2017-02-24
Genre: Mathematics
ISBN: 1498701841

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Unlike traditional books presenting stochastic processes in an academic way, this book includes concrete applications that students will find interesting such as gambling, finance, physics, signal processing, statistics, fractals, and biology. Written with an important illustrated guide in the beginning, it contains many illustrations, photos and pictures, along with several website links. Computational tools such as simulation and Monte Carlo methods are included as well as complete toolboxes for both traditional and new computational techniques.


Introduction to the Theory of Random Processes

Introduction to the Theory of Random Processes
Author: Iosif Il?ich Gikhman
Publisher: Courier Corporation
Total Pages: 537
Release: 1996-01-01
Genre: Mathematics
ISBN: 0486693872

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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.


Lectures on the Theory of Stochastic Processes

Lectures on the Theory of Stochastic Processes
Author: Anatolij V. Skorochod
Publisher: Walter de Gruyter GmbH & Co KG
Total Pages: 192
Release: 2019-01-14
Genre: Mathematics
ISBN: 3110618168

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No detailed description available for "Lectures on the Theory of Stochastic Processes".


Stochastic Processes and Filtering Theory

Stochastic Processes and Filtering Theory
Author: Andrew H. Jazwinski
Publisher: Courier Corporation
Total Pages: 404
Release: 2013-04-15
Genre: Science
ISBN: 0486318192

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This unified treatment of linear and nonlinear filtering theory presents material previously available only in journals, and in terms accessible to engineering students. Its sole prerequisites are advanced calculus, the theory of ordinary differential equations, and matrix analysis. Although theory is emphasized, the text discusses numerous practical applications as well. Taking the state-space approach to filtering, this text models dynamical systems by finite-dimensional Markov processes, outputs of stochastic difference, and differential equations. Starting with background material on probability theory and stochastic processes, the author introduces and defines the problems of filtering, prediction, and smoothing. He presents the mathematical solutions to nonlinear filtering problems, and he specializes the nonlinear theory to linear problems. The final chapters deal with applications, addressing the development of approximate nonlinear filters, and presenting a critical analysis of their performance.


Model Theory of Stochastic Processes

Model Theory of Stochastic Processes
Author: Sergio Fajardo
Publisher: Cambridge University Press
Total Pages: 136
Release: 2017-03-30
Genre: Mathematics
ISBN: 1108619266

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Since their inception, the Perspectives in Logic and Lecture Notes in Logic series have published seminal works by leading logicians. Many of the original books in the series have been unavailable for years, but they are now in print once again. In this volume, the fourteenth publication in the Lecture Notes in Logic series, Fajardo and Keisler present new research combining probability theory and mathematical logic. It is a general study of stochastic processes using ideas from model theory, a key central theme being the question, 'When are two stochastic processes alike?' The authors assume some background in nonstandard analysis, but prior knowledge of model theory and advanced logic is not necessary. This volume will appeal to mathematicians willing to explore new developments with an open mind.