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519.21 --- 536.75 --- Cluster analysis. --- Random fields --- Fields, Random --- Stochastic processes --- Correlation (Statistics) --- Multivariate analysis --- Spatial analysis (Statistics) --- Probability theory. Stochastic processes --- Entropy. Statistical thermodynamics. Irreversible processes --- 536.75 Entropy. Statistical thermodynamics. Irreversible processes --- 519.21 Probability theory. Stochastic processes --- Random fields. --- Cluster analysis
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Functional analysis --- Linear operators --- Markov processes --- Mathematical physics --- Quantum field theory --- Statistical physics
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Markov chains are an important idea, related to random walks, which crops up widely in applied stochastic analysis. They are used, for example, in performance modelling and evaluation of computer networks, queuing networks, and telecommunication systems. The main point of the present book is to provide methods, based on the construction of Lyapunov functions, of determining when a Markov chain is ergodic, null recurrent, or transient. These methods can also be extended to the study of questions of stability. Of particular concern are reflected random walks and reflected Brownian motion. The authors provide not only a self-contained introduction to the theory but also details of how the required Lyapunov functions are constructed in various situations.
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