Analyzing Markov Chains using Kronecker Products Theory and Applications /

• Main Author: Dayar, Tuğrul (Author)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic eBook
• Language: English
• Published: New York, NY : Springer New York : Imprint: Springer, 2012.
• Series: SpringerBriefs in Mathematics,
• Subjects: Mathematics.; Mathematical statistics.; Numerical analysis.; Probabilities.; Probability Theory and Stochastic Processes.; Numerical Analysis.; Probability and Statistics in Computer Science.

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...

Table of Contents:

• Introduction
• Background
• Kronecker representation
• Preprocessing
• Block iterative methods for Kronecker products
• Preconditioned projection methods
• Multilevel methods
• Decompositional methods
• Matrix analytic methods.