Markov Chains: Models, Algorithms and Applications



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Éditeur :

Springer


Paru le : 2006-06-05



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Description
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.
Pages
208 pages
Collection
n.c
Parution
2006-06-05
Marque
Springer
EAN papier
9780387293356
EAN PDF
9780387293370

Informations sur l'ebook
Nombre pages copiables
2
Nombre pages imprimables
20
Taille du fichier
1782 Ko
Prix
128,17 €

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