Markov Processes for Stochastic Modeling
- 1st Edition - September 2, 2008
- Author: Oliver Ibe
- Language: English
- Hardback ISBN:9 7 8 - 0 - 1 2 - 3 7 4 4 5 1 - 7
- Paperback ISBN:9 7 8 - 0 - 3 2 3 - 2 8 1 2 3 - 2
- eBook ISBN:9 7 8 - 0 - 0 8 - 0 9 2 2 4 5 - 4
Markov processes are used to model systems with limited memory. They are used in many areas including communications systems, transportation networks, image segmentation and… Read more
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Request a sales quoteMarkov 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
Advanced undergraduate and graduate students in engineering, science and business for whom mathematics is a problem solving tool
PrefaceAcknowledgments1. Basic Concepts 2. Introduction to Markov Processes 3. Discrete-Time Markov Chains 4. Continuous-Time Markov Chains 5. Markovian Queueing Systems 6. Markov Renewal Processes7. Markovian Arrival Processes 8. Random Walk9. Brownian Motion and Diffusion Processes 10. Controlled Markov Processes11. Hidden Markov Models 12. Markov Random Fields 13. Markov Point Processes 14. Markov Chain Monte Carlo ReferencesIndex
- No. of pages: 512
- Language: English
- Edition: 1
- Published: September 2, 2008
- Imprint: Academic Press
- Hardback ISBN: 9780123744517
- Paperback ISBN: 9780323281232
- eBook ISBN: 9780080922454
OI
Oliver Ibe
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.
Affiliations and expertise
University of Massachusetts, Lowell, USA