Markov Processes for Stochastic Modeling
Ibe, Oliver
ISBN 10: 0123744512 ISBN 13: 9780123744517
Published by Academic Press (edition 1), 2008
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Hardcover
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About this Item
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It's a preowned item in good condition and includes all the pages. It may have some general signs of wear and tear, such as markings, highlighting, slight damage to the cover, minimal wear to the binding, etc., but they will not affect the overall reading experience. Seller Inventory # 0123744512-11-1
Synopsis:
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. In addition to traditional topics such as Markovian queueing system, the book discusses such topics as continuous-time random walk,correlated random walk, Brownian motion, diffusion processes, hidden Markov models, Markov random fields, Markov point processes and Markov chain Monte Carlo. Continuous-time random walk is currently used in econophysics to model the financial market, which has traditionally been modelled as a Brownian motion. Correlated random walk is popularly used in ecological studies to model animal and insect movement. Hidden Markov models are used in speech analysis and DNA sequence analysis while Markov random fields and Markov point processes are used in image analysis. Thus, the book is designed to have a very broad appeal.
- Provides the practical, current applications of Markov processes
- Coverage of HMM, Point processes, and Monte Carlo- Includes enough theory to help students gain throrough understanding of the subject
- Principles can be immediately applied in many specific research projects, saving researchers time
- End of chapter exercises provide reinforcement, practice and increased understanding to the student
About the Author: Dr Ibe has been teaching at U Mass since 2003. He also has more than 20 years of experience in the corporate world, most recently as Chief Technology Officer at Sineria Networks and Director of Network Architecture for Spike Broadband Corp.
"About this title" may belong to another edition of this title.
Bibliographic Details
Title: Markov Processes for Stochastic Modeling
Publisher: Academic Press (edition 1)
Publication Date: 2008
Binding: Hardcover
Condition: Good
Edition: 1.
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Markov Processes for Stochastic Modeling
Print on DemandSeller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
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Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. In addition to traditional topics such as Markovian queueing system, the book discusses such topics as continuous-time random walk,correlated random walk, Brownian motion, diffusion processes, hidden Markov models, Markov random fields, Markov point processes and Markov chain Monte Carlo. Continuous-time random walk is currently used in econophysics to model the financial market, which has traditionally been modelled as a Brownian motion. Correlated random walk is popularly used in ecological studies to model animal and insect movement. Hidden Markov models are used in speech analysis and DNA sequence analysis while Markov random fields and Markov point processes are used in image analysis. Thus, the book is designed to have a very broad appeal.- Provides the practical, current applications of Markov processes- Coverage of HMM, Point processes, and Monte Carlo- Includes enough theory to help students gain throrough understanding of the subject- Principles can be immediately applied in many specific research projects, saving researchers time- End of chapter exercises provide reinforcement, practice and increased understanding to the student 512 pp. Englisch. Seller Inventory # 9780123744517
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Markov Processes for Stochastic Modeling
Print on DemandSeller: AHA-BUCH GmbH, Einbeck, Germany
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Buch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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. In addition to traditional topics such as Markovian queueing system, the book discusses such topics as continuous-time random walk,correlated random walk, Brownian motion, diffusion processes, hidden Markov models, Markov random fields, Markov point processes and Markov chain Monte Carlo. Continuous-time random walk is currently used in econophysics to model the financial market, which has traditionally been modelled as a Brownian motion. Correlated random walk is popularly used in ecological studies to model animal and insect movement. Hidden Markov models are used in speech analysis and DNA sequence analysis while Markov random fields and Markov point processes are used in image analysis. Thus, the book is designed to have a very broad appeal.- Provides the practical, current applications of Markov processes- Coverage of HMM, Point processes, and Monte Carlo- Includes enough theory to help students gain throrough understanding of the subject- Principles can be immediately applied in many specific research projects, saving researchers time- End of chapter exercises provide reinforcement, practice and increased understanding to the student. Seller Inventory # 9780123744517
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Markov Processes for Stochastic Modeling
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Hardcover. Condition: Very Good. No Jacket. May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less. Seller Inventory # G0123744512I4N00