Markov processes for stochastic modeling /
Author / Creator: | Ibe, Oliver C. (Oliver Chukwudi), 1947- author. |
---|---|
Edition: | Second edition. |
Imprint: | London : Elsevier, 2013. |
Description: | 1 online resource (xviii, 494 pages). |
Language: | English |
Series: | Elsevier insights Elsevier insights. |
Subject: | |
Format: | E-Resource Book |
URL for this record: | http://pi.lib.uchicago.edu/1001/cat/bib/11191158 |
Summary: | 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. |
---|---|
Physical Description: | 1 online resource (xviii, 494 pages). |
Bibliography: | Includes bibliographical references. |
ISBN: | 9780124077959 0124077951 9780124078390 0124078397 |