Analyzing Markov Chains using Kronecker Products Theory and Applications /

Kronecker products are used to define the underlying Markov chain (MC) in various modeling formalisms, including compositional Markovian models, hierarchical Markovian models, and stochastic process algebras. The motivation behind using a Kronecker structured representation rather than a flat one is...

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Bibliographic Details
Call Number:Libro Electrónico
Main Author: Dayar, Tugrul (Author)
Corporate Author: SpringerLink (Online service)
Format: Electronic eBook
Language:Inglés
Published: New York, NY : Springer New York : Imprint: Springer, 2012.
Edition:1st ed. 2012.
Series:SpringerBriefs in Mathematics,
Subjects:
Probabilities.
Numerical analysis.
Computer science-Mathematics.
Mathematical statistics.
Probability Theory.
Numerical Analysis.
Probability and Statistics in Computer Science.
Online Access:Texto Completo
Table of Contents:
  • Introduction
  • Background
  • Kronecker representation
  • Preprocessing
  • Block iterative methods for Kronecker products
  • Preconditioned projection methods
  • Multilevel methods
  • Decompositional methods
  • Matrix analytic methods.

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