
- 514 pages
- English
- ePUB (mobile friendly)
- Available on iOS & Android
eBook - ePub
Markov Processes for Stochastic Modeling
About this book
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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Please note we cannot support devices running on iOS 13 and Android 7 or earlier. Learn more about using the app.
Yes, you can access Markov Processes for Stochastic Modeling by Oliver Ibe in PDF and/or ePUB format, as well as other popular books in Mathematics & History & Philosophy of Mathematics. We have over one million books available in our catalogue for you to explore.
Information
Table of contents
- Cover image
- Title page
- Table of Contents
- Copyright
- Acknowledgments
- Preface to the Second Edition
- Preface to the First Edition
- 1. Basic Concepts in Probability
- 2. Basic Concepts in Stochastic Processes
- 3. Introduction to Markov Processes
- 4. Discrete-Time Markov Chains
- 5. Continuous-Time Markov Chains
- 6. Markov Renewal Processes
- 7. Markovian Queueing Systems
- 8. Random Walk
- 9. Brownian Motion
- 10. Diffusion Processes
- 11. Levy Processes
- 12. Markovian Arrival Processes
- 13. Controlled Markov Processes
- 14. Hidden Markov Models
- 15. Markov Point Processes
- References