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Generalized Stochastic Processes

Generalized Stochastic Processes PDF

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Author: Stefan Schäffler
Publisher: Springer
ISBN: 3319787683
Size: 65.47 MB
Format: PDF, ePub
Category : Mathematics
Languages : en
Pages : 183
View: 1241


This textbook shall serve a double purpose: first of all, it is a book about generalized stochastic processes, a very important but highly neglected part of probability theory which plays an outstanding role in noise modelling. Secondly, this textbook is a guide to noise modelling for mathematicians and engineers to foster the interdisciplinary discussion between mathematicians (to provide effective noise models) and engineers (to be familiar with the mathematical backround of noise modelling in order to handle noise models in an optimal way).Two appendices on "A Short Course in Probability Theory" and "Spectral Theory of Stochastic Processes" plus a well-choosen set of problems and solutions round this compact textbook off.

Stochastic Models Analysis And Applications

Stochastic Models  Analysis and Applications PDF

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Author: B. R. Bhat
Publisher: New Age International
ISBN: 9788122412284
Size: 46.10 MB
Format: PDF, Docs
Category : Mathematical statistics
Languages : en
Pages : 408
View: 6225


The Book Presents A Systematic Exposition Of The Basic Theory And Applications Of Stochastic Models.Emphasising The Modelling Rather Than Mathematical Aspects Of Stochastic Processes, The Book Bridges The Gap Between The Theory And Applications Of These Processes.The Basic Building Blocks Of Model Construction Are Explained In A Step By Step Manner, Starting From The Simplest Model Of Random Walk And Proceeding Gradually To More Complicated Models. Several Examples Are Given Throughout The Text To Illustrate Important Analytical Properties As Well As To Provide Applications.The Book Also Includes A Detailed Chapter On Inference For Stochastic Processes. This Chapter Highlights Some Of The Recent Developments In The Subject And Explains Them Through Illustrative Examples.An Important Feature Of The Book Is The Complements And Problems Section At The End Of Each Chapter Which Presents (I) Additional Properties Of The Model, (Ii) Extensions Of The Model, And (Iii) Applications Of The Model To Different Areas.With All These Features, This Is An Invaluable Text For Post-Graduate Students Of Statistics, Mathematics And Operation Research.

Ars S

ARS S  PDF

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Author:
Publisher:
ISBN:
Size: 26.15 MB
Format: PDF
Category : Agriculture
Languages : en
Pages :
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Modelling And Application Of Stochastic Processes

Modelling and Application of Stochastic Processes PDF

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Author: Uday B. Desai
Publisher: Springer Science & Business Media
ISBN: 9780898381771
Size: 18.47 MB
Format: PDF, ePub, Docs
Category : Science
Languages : en
Pages : 288
View: 4728


The subject of modelling and application of stochastic processes is too vast to be exhausted in a single volume. In this book, attention is focused on a small subset of this vast subject. The primary emphasis is on realization and approximation of stochastic systems. Recently there has been considerable interest in the stochastic realization problem, and hence, an attempt has been made here to collect in one place some of the more recent approaches and algorithms for solving the stochastic realiza tion problem. Various different approaches for realizing linear minimum-phase systems, linear nonminimum-phase systems, and bilinear systems are presented. These approaches range from time-domain methods to spectral-domain methods. An overview of the chapter contents briefly describes these approaches. Also, in most of these chapters special attention is given to the problem of developing numerically ef ficient algorithms for obtaining reduced-order (approximate) stochastic realizations. On the application side, chapters on use of Markov random fields for modelling and analyzing image signals, use of complementary models for the smoothing problem with missing data, and nonlinear estimation are included. Chapter 1 by Klein and Dickinson develops the nested orthogonal state space realization for ARMA processes. As suggested by the name, nested orthogonal realizations possess two key properties; (i) the state variables are orthogonal, and (ii) the system matrices for the (n + l)st order realization contain as their "upper" n-th order blocks the system matrices from the n-th order realization (nesting property).

Modeling And Analysis Of Stochastic Systems Third Edition

Modeling and Analysis of Stochastic Systems  Third Edition PDF

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Author: Vidyadhar G. Kulkarni
Publisher: CRC Press
ISBN: 1498756727
Size: 34.75 MB
Format: PDF
Category : Business & Economics
Languages : en
Pages : 606
View: 5153


Building on the author’s more than 35 years of teaching experience, Modeling and Analysis of Stochastic Systems, Third Edition, covers the most important classes of stochastic processes used in the modeling of diverse systems. For each class of stochastic process, the text includes its definition, characterization, applications, transient and limiting behavior, first passage times, and cost/reward models. The third edition has been updated with several new applications, including the Google search algorithm in discrete time Markov chains, several examples from health care and finance in continuous time Markov chains, and square root staffing rule in Queuing models. More than 50 new exercises have been added to enhance its use as a course text or for self-study. The sequence of chapters and exercises has been maintained between editions, to enable those now teaching from the second edition to use the third edition. Rather than offer special tricks that work in specific problems, this book provides thorough coverage of general tools that enable the solution and analysis of stochastic models. After mastering the material in the text, readers will be well-equipped to build and analyze useful stochastic models for real-life situations.

Stochastic Models In Operations Research

Stochastic Models in Operations Research PDF

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Author: Daniel P. Heyman
Publisher: Courier Corporation
ISBN: 9780486432595
Size: 57.68 MB
Format: PDF, ePub, Mobi
Category : Mathematics
Languages : en
Pages : 547
View: 6313


This volume of a 2-volume set explores the central facts and ideas of stochastic processes, illustrating their use in models based on applied and theoretical investigations. Explores stochastic processes, operating characteristics of stochastic systems, and stochastic optimization. Comprehensive in its scope, this graduate-level text emphasizes the practical importance, intellectual stimulation, and mathematical elegance of stochastic models.

Basics Of Applied Stochastic Processes

Basics of Applied Stochastic Processes PDF

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Author: Richard Serfozo
Publisher: Springer Science & Business Media
ISBN: 3540893326
Size: 21.59 MB
Format: PDF, ePub, Mobi
Category : Mathematics
Languages : en
Pages : 443
View: 2947


Stochastic processes are mathematical models of random phenomena that evolve according to prescribed dynamics. Processes commonly used in applications are Markov chains in discrete and continuous time, renewal and regenerative processes, Poisson processes, and Brownian motion. This volume gives an in-depth description of the structure and basic properties of these stochastic processes. A main focus is on equilibrium distributions, strong laws of large numbers, and ordinary and functional central limit theorems for cost and performance parameters. Although these results differ for various processes, they have a common trait of being limit theorems for processes with regenerative increments. Extensive examples and exercises show how to formulate stochastic models of systems as functions of a system’s data and dynamics, and how to represent and analyze cost and performance measures. Topics include stochastic networks, spatial and space-time Poisson processes, queueing, reversible processes, simulation, Brownian approximations, and varied Markovian models. The technical level of the volume is between that of introductory texts that focus on highlights of applied stochastic processes, and advanced texts that focus on theoretical aspects of processes.

Mathematical Economics And Operations Research

Mathematical Economics and Operations Research PDF

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Author: Joseph Zaremba
Publisher: Gale Cengage
ISBN:
Size: 75.52 MB
Format: PDF
Category : Economics
Languages : en
Pages : 606
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Statistics Of Random Processes

Statistics of Random Processes PDF

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Author: Robert S. Liptser
Publisher: Springer Science & Business Media
ISBN: 3662130432
Size: 26.48 MB
Format: PDF, ePub, Docs
Category : Mathematics
Languages : en
Pages : 427
View: 4297


These volumes cover non-linear filtering (prediction and smoothing) theory and its applications to the problem of optimal estimation, control with incomplete data, information theory, and sequential testing of hypothesis. Also presented is the theory of martingales, of interest to those who deal with problems in financial mathematics. These editions include new material, expanded chapters, and comments on recent progress in the field.

Numerical Modelling Of Random Processes And Fields

Numerical Modelling of Random Processes and Fields PDF

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Author: Vitaliĭ Antonovich Ogorodnikov
Publisher: VSP
ISBN: 9789067641999
Size: 21.76 MB
Format: PDF, ePub, Mobi
Category : Mathematics
Languages : en
Pages : 240
View: 6248


Computer-aided modelling is one of the most effective means of getting to the root of a natural phenomenon and of predicting the consequences of human impact on the environment. General methods of numerical modelling of random processes have been effectively developed and the area of applications has rapidly expanded in recent years. This book deals with the development and investigation of numerical methods for simulation of random processes and fields. The book opens with a description of scalar and vector-valued Gaussian models, followed by non-Gaussian models. Furthermore, issues of convergence of approximate models of random fields are studied. The last part of this book is devoted to applications of stochastic modelling, in which new application areas such as simulation of meteorological processes and fields, sea surface undulation, and stochastic structure of clouds, are presented.

Stochastic Processes Modeling And Simulation

Stochastic Processes  Modeling and Simulation PDF

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Author: D N Shanbhag
Publisher: Gulf Professional Publishing
ISBN: 9780444500137
Size: 18.23 MB
Format: PDF, ePub, Mobi
Category : Mathematics
Languages : en
Pages : 1000
View: 468


This sequel to volume 19 of Handbook on Statistics on Stochastic Processes: Modelling and Simulation is concerned mainly with the theme of reviewing and, in some cases, unifying with new ideas the different lines of research and developments in stochastic processes of applied flavour. This volume consists of 23 chapters addressing various topics in stochastic processes. These include, among others, those on manufacturing systems, random graphs, reliability, epidemic modelling, self-similar processes, empirical processes, time series models, extreme value therapy, applications of Markov chains, modelling with Monte Carlo techniques, and stochastic processes in subjects such as engineering, telecommunications, biology, astronomy and chemistry. particular with modelling, simulation techniques and numerical methods concerned with stochastic processes. The scope of the project involving this volume as well as volume 19 is already clarified in the preface of volume 19. The present volume completes the aim of the project and should serve as an aid to students, teachers, researchers and practitioners interested in applied stochastic processes.

Stochastic Processes With Applications To Finance

Stochastic Processes with Applications to Finance PDF

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Author: Masaaki Kijima
Publisher: CRC Press
ISBN: 9781584882244
Size: 57.88 MB
Format: PDF, ePub
Category : Mathematics
Languages : en
Pages : 288
View: 668


In recent years, modeling financial uncertainty using stochastic processes has become increasingly important, but it is commonly perceived as requiring a deep mathematical background. Stochastic Processes with Applications to Finance shows that this is not necessarily so. It presents the theory of discrete stochastic processes and their applications in finance in an accessible treatment that strikes a balance between the abstract and the practical. Using an approach that views sophisticated stochastic calculus as based on a simple class of discrete processes-"random walks"-the author first provides an elementary introduction to the relevant areas of real analysis and probability. He then uses random walks to explain the change of measure formula, the reflection principle, and the Kolmogorov backward equation. The Black-Scholes formula is derived as a limit of binomial model, and applications to the pricing of derivative securities are presented. Another primary focus of the book is the pricing of corporate bonds and credit derivatives, which the author explains in terms of discrete default models. By presenting important results in discrete processes and showing how to transfer those results to their continuous counterparts, Stochastic Processes with Applications to Finance imparts an intuitive and practical understanding of the subject. This unique treatment is ideal both as a text for a graduate-level class and as a reference for researchers and practitioners in financial engineering, operations research, and mathematical and statistical finance.

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