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By Tugrul Dayar

Kronecker items are used to outline the underlying Markov chain (MC) in numerous modeling formalisms, together with compositional Markovian types, hierarchical Markovian types, and stochastic technique algebras. the inducement at the back of utilizing a Kronecker dependent illustration instead of a flat one is to relieve the garage requisites linked to the MC. With this process, platforms which are an order of significance better may be analyzed at the comparable platform. The advancements within the resolution of such MCs are reviewed from an algebraic perspective and attainable components for extra study are indicated with an emphasis on preprocessing utilizing reordering, grouping, and lumping and numerical research utilizing block iterative, preconditioned projection, multilevel, decompositional, and matrix analytic tools. Case experiences from closed queueing networks and stochastic chemical kinetics are supplied to encourage decompositional and matrix analytic tools, respectively.

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Analyzing Markov Chains using Kronecker Products: Theory and Applications (SpringerBriefs in Mathematics) by Tugrul Dayar


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