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Markov Chains: Models, Algorithms and Applications.

Markov Chains: Models, Algorithms and Applications.

Markov Chains: Models, Algorithms and Applications.
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Markov Chains: Models, Algorithms and Applications. Hardback - 2006 - 2006th Edition

by Ching, Wai-Ki; Michael K. Ng

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  • Hardback

Description

2006. Berlin, Springer, 2006. 18 illus., XIV, 205 P. Hardcover. Versand aus Deutschland / We dispatch from Germany via Air Mail. Einband bestoßen, daher Mängelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. Stamped.
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Details

  • Title Markov Chains: Models, Algorithms and Applications.
  • Author Ching, Wai-Ki; Michael K. Ng
  • Binding Hardback
  • Edition number 2006th
  • Edition 2006
  • Pages 18 illus., XIV, 205 P.
  • Volumes 1
  • Language ENG
  • Publisher Springer
  • Publication date 2006
  • Illustrated Yes
  • Bookseller's Inventory # 7075DB
  • ISBN 9780387293356 / 0387293353
  • Weight 1.08 lbs (0.49 kg)
  • Dimensions 9.21 x 6.14 x 0.56 in (23.39 x 15.60 x 1.42 cm)
  • Category Mathematics
  • Library of Congress subjects Markov processes, Algorithms
  • Library of Congress Catalogue Number 2005933263
  • Dewey Decimal Code 519.233

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Reader reviews for Markov Chains: Models, Algorithms and Applications.

From the publisher

Markov chains is 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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