Continuous-Time Markov Chains and Applications: A Two-Time-Scale Approach: 37 (Stochastic Modelling and Applied Probability, 37) - Image 1

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Springer Continuous-Time Markov Chains and Applications: A Two-Time-Scale Approach: 37 (Stochastic Modelling and Applied Probability, 37)

Name: Continuous-Time Markov Chains and Applications: A Two-Time-Scale Approach: 37 (Stochastic Modelling and Applied Probability, 37)
Brand: Springer
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Managers' Guides to Computing

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This book gives a systematic treatment of singularly perturbed systems that naturally arise in control and optimization, queueing networks, manufacturing systems, and financial engineering. It presents results on asymptotic expansions of solutions of Komogorov forward and backward equations, properties of functional occupation measures, exponential upper bounds, and functional limit results for Markov chains with weak and strong interactions. To bridge the gap between theory and applications, a large portion of the book is devoted to applications in controlled dynamic systems, production planning, and numerical methods for controlled Markovian systems with large-scale and complex structures in the real-world problems. This second edition has been updated throughout and includes two new chapters on asymptotic expansions of solutions for backward equations and hybrid LQG problems. The chapters on analytic and probabilistic properties of two-time-scale Markov chains have been almost completely rewritten and the notation has been streamlined and simplified. This book is written for applied mathematicians, engineers, operations researchers, and applied scientists. Selected material from the book can also be used for a one semester advanced graduate-level course in applied probability and stochastic processes.

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Brand: Springer
Format: hardcover
ASIN: 1461443458
Category: Books > Subjects > Business, Finance & Law > E-Commerce > Managers' Guides to Computing
Domain: Amazon UK
Release Date: 25 October 2012
Listed Since: 26 April 2012

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Springer Continuous-Time Markov Chains and Applications: A Two-Time-Scale Approach: 37 (Stochastic Modelling and Applied Probability, 37)

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