Markov processes for stochastic modeling
by Ibe, Oliver C., (Oliver Chukwudi)
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 u…
Read More ↓Title Statements
- Full title :Markov processes for stochastic modeling / Oliver C. Ibe.
Summary
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 M.
Read More ↓Edition Statements
- Publication Date:©2009.
Publication Statements
- Publisher(s):Academic Press
- Place of Publication:Amsterdam
- Language:eng
- Publication Date:©2009.
The Physical Object
- Description:1 online resource (xiv, 490 pages) : : illustrations
Edition Identifiers
- ISBN:9780080922454, 0080922457
- oclc:ocn664573250
- LC Classification:QA274.7
- Dewey Decimal:519.2/33
Table of Contents
Basic concepts -- Introduction to Markov processes -- Discrete-time Markov chains -- Continuous-time Markov chains -- Markovian queueing systems -- Markov renewal processes -- Markovian arrival processes -- Random walk -- Brownian motion and diffusion processes -- Controlled Markov processes -- Hidden Markov models -- Markov random fields -- Markov point processes -- Markov chain Monte Carlo.
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