Markov Processes for Stochastic Modeling

Oliver Ibe

ISBN 10: 0323282954 / ISBN 13: 9780323282956

Published by Elsevier, 2013

About this Item

Markov Processes for Stochastic Modeling | Oliver Ibe | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2013 | Elsevier | EAN 9780323282956 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

Seller Inventory # 103709277

Bibliographic Details

• Title: Markov Processes for Stochastic Modeling
• Publisher: Elsevier
• Publication Date: 2013
• Language: English
• ISBN 10: 0323282954
• ISBN 13: 9780323282956
• Binding: Taschenbuch
• Edition: 2nd Edition
• Condition: Neu
• Dimensions: 24W x 152H x 229D millimeters 24 millimeters width by 152 millimeters height by 229 millimeters depth
• Weight: 450 grams
• Seller catalogs:
  • Bücher

About this title

Synopsis

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.

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.