Markov Processes for Stochastic Modeling

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  • Publisher : Newnes
  • Release : 22 May 2013
  • ISBN : 9780124078390
  • Page : 514 pages
  • Rating : 4.5/5 from 103 voters

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Markov processes are processes that have limited memory. In particular, their dependence on the past is only through the previous state. They are used to model the behavior of many systems including communications systems, transportation networks, image segmentation and analysis, biological systems and DNA sequence analysis, random atomic motion and diffusion in physics, social mobility, population studies, epidemiology, animal and insect migration, queueing systems, resource management, dams, financial engineering, actuarial science, and decision systems. Covering a wide range of areas of application of Markov processes, this second edition is revised to highlight the most important aspects as well as the most recent trends and applications of Markov processes. The author spent over 16 years in the industry before returning to academia, and he has applied many of the principles covered in this book in multiple research projects. Therefore, this is an applications-oriented book that also includes enough theory to provide a solid ground in the subject for the reader. Presents both the theory and applications of the different aspects of Markov processes Includes numerous solved examples as well as detailed diagrams that make it easier to understand the principle being presented Discusses different applications of hidden Markov models, such as DNA sequence analysis and speech analysis.

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Markov Processes for Stochastic Modeling

Markov Processes for Stochastic Modeling
  • Author : Oliver Ibe
  • Publisher : Newnes
  • Release Date : 2013-05-22
  • ISBN : 9780124078390
GET THIS BOOKMarkov Processes for Stochastic Modeling

Markov processes are processes that have limited memory. In particular, their dependence on the past is only through the previous state. They are used to model the behavior of many systems including communications systems, transportation networks, image segmentation and analysis, biological systems and DNA sequence analysis, random atomic motion and diffusion in physics, social mobility, population studies, epidemiology, animal and insect migration, queueing systems, resource management, dams, financial engineering, actuarial science, and decision systems. Covering a wide range of areas

Markov Processes for Stochastic Modeling

Markov Processes for Stochastic Modeling
  • Author : Oliver Ibe
  • Publisher : Academic Press
  • Release Date : 2008-09-02
  • ISBN : 9780080922454
GET THIS BOOKMarkov Processes for Stochastic Modeling

Markov processes are used to model systems with limited memory. They are used in many areas including communications systems, transportation networks, image segmentation and analysis, biological systems and DNA sequence analysis, random atomic motion and diffusion in physics, social mobility, population studies, epidemiology, animal and insect migration, queueing systems, resource management, dams, financial engineering, actuarial science, and decision systems. This book, which is written for upper level undergraduate and graduate students, and researchers, presents a unified presentation of Markov processes.

An Introduction to Stochastic Modeling

An Introduction to Stochastic Modeling
  • Author : Howard M. Taylor,Samuel Karlin
  • Publisher : Academic Press
  • Release Date : 2014-05-10
  • ISBN : 9781483269276
GET THIS BOOKAn Introduction to Stochastic Modeling

An Introduction to Stochastic Modeling provides information pertinent to the standard concepts and methods of stochastic modeling. This book presents the rich diversity of applications of stochastic processes in the sciences. Organized into nine chapters, this book begins with an overview of diverse types of stochastic models, which predicts a set of possible outcomes weighed by their likelihoods or probabilities. This text then provides exercises in the applications of simple stochastic analysis to appropriate problems. Other chapters consider the study

Stochastic Modelling of Social Processes

Stochastic Modelling of Social Processes
  • Author : Andreas Diekmann,Peter Mitter
  • Publisher : Academic Press
  • Release Date : 2014-05-10
  • ISBN : 9781483266565
GET THIS BOOKStochastic Modelling of Social Processes

Stochastic Modelling of Social Processes provides information pertinent to the development in the field of stochastic modeling and its applications in the social sciences. This book demonstrates that stochastic models can fulfill the goals of explanation and prediction. Organized into nine chapters, this book begins with an overview of stochastic models that fulfill normative, predictive, and structural–analytic roles with the aid of the theory of probability. This text then examines the study of labor market structures using analysis of

Stochastic Modeling

Stochastic Modeling
  • Author : Nicolas Lanchier
  • Publisher : Springer
  • Release Date : 2017-01-27
  • ISBN : 9783319500386
GET THIS BOOKStochastic Modeling

Three coherent parts form the material covered in this text, portions of which have not been widely covered in traditional textbooks. In this coverage the reader is quickly introduced to several different topics enriched with 175 exercises which focus on real-world problems. Exercises range from the classics of probability theory to more exotic research-oriented problems based on numerical simulations. Intended for graduate students in mathematics and applied sciences, the text provides the tools and training needed to write and use programs

Constrained Markov Decision Processes

Constrained Markov Decision Processes
  • Author : Eitan Altman
  • Publisher : CRC Press
  • Release Date : 1999-03-30
  • ISBN : 0849303826
GET THIS BOOKConstrained Markov Decision Processes

This book provides a unified approach for the study of constrained Markov decision processes with a finite state space and unbounded costs. Unlike the single controller case considered in many other books, the author considers a single controller with several objectives, such as minimizing delays and loss, probabilities, and maximization of throughputs. It is desirable to design a controller that minimizes one cost objective, subject to inequality constraints on other cost objectives. This framework describes dynamic decision problems arising frequently

Markov Models & Optimization

Markov Models & Optimization
  • Author : M.H.A. Davis
  • Publisher : Routledge
  • Release Date : 2018-02-19
  • ISBN : 9781351433495
GET THIS BOOKMarkov Models & Optimization

This book presents a radically new approach to problems of evaluating and optimizing the performance of continuous-time stochastic systems. This approach is based on the use of a family of Markov processes called Piecewise-Deterministic Processes (PDPs) as a general class of stochastic system models. A PDP is a Markov process that follows deterministic trajectories between random jumps, the latter occurring either spontaneously, in a Poisson-like fashion, or when the process hits the boundary of its state space. This formulation includes

Probability and Stochastic Modeling

Probability and Stochastic Modeling
  • Author : Vladimir I. Rotar
  • Publisher : CRC Press
  • Release Date : 2012-08-25
  • ISBN : 9781439872062
GET THIS BOOKProbability and Stochastic Modeling

A First Course in Probability with an Emphasis on Stochastic Modeling Probability and Stochastic Modeling not only covers all the topics found in a traditional introductory probability course, but also emphasizes stochastic modeling, including Markov chains, birth-death processes, and reliability models. Unlike most undergraduate-level probability texts, the book also focuses on increasingly important areas, such as martingales, classification of dependency structures, and risk evaluation. Numerous examples, exercises, and models using real-world data demonstrate the practical possibilities and restrictions of different

Stochastic Models with Applications to Genetics, Cancers, AIDS and Other Biomedical Systems

Stochastic Models with Applications to Genetics, Cancers, AIDS and Other Biomedical Systems
  • Author : Wai-Yuan Tan
  • Publisher : World Scientific
  • Release Date : 2002-02-26
  • ISBN : 9789814489317
GET THIS BOOKStochastic Models with Applications to Genetics, Cancers, AIDS and Other Biomedical Systems

This book presents a systematic treatment of Markov chains, diffusion processes and state space models, as well as alternative approaches to Markov chains through stochastic difference equations and stochastic differential equations. It illustrates how these processes and approaches are applied to many problems in genetics, carcinogenesis, AIDS epidemiology and other biomedical systems. One feature of the book is that it describes the basic MCMC (Markov chain and Monte Carlo) procedures and illustrates how to use the Gibbs sampling method and

Stochastic Modelling in Process Technology

Stochastic Modelling in Process Technology
  • Author : Herold G. Dehling,Timo Gottschalk,Alex C. Hoffmann
  • Publisher : Elsevier
  • Release Date : 2007-07-03
  • ISBN : 0080548970
GET THIS BOOKStochastic Modelling in Process Technology

There is an ever increasing need for modelling complex processes reliably. Computational modelling techniques, such as CFD and MD may be used as tools to study specific systems, but their emergence has not decreased the need for generic, analytical process models. Multiphase and multicomponent systems, and high-intensity processes displaying a highly complex behaviour are becoming omnipresent in the processing industry. This book discusses an elegant, but little-known technique for formulating process models in process technology: stochastic process modelling. The technique

Stochastic Modeling

Stochastic Modeling
  • Author : Barry L. Nelson
  • Publisher : Courier Corporation
  • Release Date : 2012-10-11
  • ISBN : 9780486139944
GET THIS BOOKStochastic Modeling

Coherent introduction to techniques also offers a guide to the mathematical, numerical, and simulation tools of systems analysis. Includes formulation of models, analysis, and interpretation of results. 1995 edition.

Markov Chains and Stochastic Stability

Markov Chains and Stochastic Stability
  • Author : Sean Meyn,Richard L. Tweedie
  • Publisher : Cambridge University Press
  • Release Date : 2009-04-02
  • ISBN : 9780521731829
GET THIS BOOKMarkov Chains and Stochastic Stability

New up-to-date edition of this influential classic on Markov chains in general state spaces. Proofs are rigorous and concise, the range of applications is broad and knowledgeable, and key ideas are accessible to practitioners with limited mathematical background. New commentary by Sean Meyn, including updated references, reflects developments since 1996.

Stochastic Modelling of Reaction-Diffusion Processes

Stochastic Modelling of Reaction-Diffusion Processes
  • Author : Radek Erban,S. Jonathan Chapman
  • Publisher : Cambridge University Press
  • Release Date : 2020-01-30
  • ISBN : 9781108498128
GET THIS BOOKStochastic Modelling of Reaction-Diffusion Processes

Practical introduction for advanced undergraduate or beginning graduate students of applied mathematics, developed at the University of Oxford.

Statistical Topics and Stochastic Models for Dependent Data with Applications

Statistical Topics and Stochastic Models for Dependent Data with Applications
  • Author : Vlad Stefan Barbu,Nicolas Vergne
  • Publisher : John Wiley & Sons
  • Release Date : 2020-12-03
  • ISBN : 9781786306036
GET THIS BOOKStatistical Topics and Stochastic Models for Dependent Data with Applications

This book is a collective volume authored by leading scientists in the field of stochastic modelling, associated statistical topics and corresponding applications. The main classes of stochastic processes for dependent data investigated throughout this book are Markov, semi-Markov, autoregressive and piecewise deterministic Markov models. The material is divided into three parts corresponding to: (i) Markov and semi-Markov processes, (ii) autoregressive processes and (iii) techniques based on divergence measures and entropies. A special attention is payed to applications in reliability, survival

Elements of Stochastic Modelling

Elements of Stochastic Modelling
  • Author : Konstantin Borovkov
  • Publisher : World Scientific Publishing Company
  • Release Date : 2014-06-30
  • ISBN : 9789814571180
GET THIS BOOKElements of Stochastic Modelling

This is the expanded second edition of a successful textbook that provides a broad introduction to important areas of stochastic modelling. The original text was developed from lecture notes for a one-semester course for third-year science and actuarial students at the University of Melbourne. It reviewed the basics of probability theory and then covered the following topics: Markov chains, Markov decision processes, jump Markov processes, elements of queueing theory, basic renewal theory, elements of time series and simulation. The present