Markov Chains: Models, Algorithms and Applications

Download or Read eBook Markov Chains: Models, Algorithms and Applications PDF written by Wai-Ki Ching and published by Springer Science & Business Media. This book was released on 2006-06-05 with total page 212 pages. Available in PDF, EPUB and Kindle.
Markov Chains: Models, Algorithms and Applications
Author :
Publisher : Springer Science & Business Media
Total Pages : 212
Release :
ISBN-10 : 9780387293370
ISBN-13 : 038729337X
Rating : 4/5 (70 Downloads)

Book Synopsis Markov Chains: Models, Algorithms and Applications by : Wai-Ki Ching

Book excerpt: Markov chains are a particularly powerful and widely used tool for analyzing a variety of stochastic (probabilistic) systems over time. This monograph will present a series of Markov models, starting from the basic models and then building up to higher-order models. Included in the higher-order discussions are multivariate models, higher-order multivariate models, and higher-order hidden models. In each case, the focus is on the important kinds of applications that can be made with the class of models being considered in the current chapter. Special attention is given to numerical algorithms that can efficiently solve the models. Therefore, Markov Chains: Models, Algorithms and Applications outlines recent developments of Markov chain models for modeling queueing sequences, Internet, re-manufacturing systems, reverse logistics, inventory systems, bio-informatics, DNA sequences, genetic networks, data mining, and many other practical systems.


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