Items related to Markov Processes for Stochastic Modeling
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
"synopsis" may belong to another edition of this title.
Review
"It is a good textbook for students and reference book for researchers and practitioners, it provides an introduction to a wide range of topics including the classical and the most actual ones, and the reader who is interested in more information in any particular topic is advised to consult any of specialized books in the references." -- Laszlo Lakatos (Budapest), Zentralblatt MATH
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.
- PublisherAcademic Press
- Publication date2008
- ISBN 10 0123744512
- ISBN 13 9780123744517
- BindingHardcover
- LanguageEnglish
- Number of pages512
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Markov Processes for Stochastic Modeling
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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
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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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Academic Press (edition 1), 2008
ISBN 10: 0123744512
ISBN 13: 9780123744517
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