Reversibility and Stochastic Networks
by F.P. Kelly
Publisher: John Wiley and Sons Ltd 1979
ISBN/ASIN: 1107401151
Number of pages: 233
Description:
Examines the behavior in equilibrium of vector stochastic processes or stochastic networks, considering a wide range of applications by discussing stochastic models that arise in fields such as operational research, biology, and polymer science. Reviews the concept of reversibility, including material necessary to establish terminology and notation. Explains such uses as the study of the output from a queue, the flow of current in a conductor, the age of an allele, and the equilibrium distribution of a polymerization process. Also examines the extent to which the assumption of reversibility can be relaxed without destroying the associated tractability. Requires an understanding of Markov processes.
Download or read it online for free here:
Download link
(multiple formats)
Similar books
Lectures on Stochastic Differential Equations and Malliavin Calculusby S. Watanabe - Tata Institute of Fundamental Research
The author's main purpose in these lectures was to study solutions of stochastic differential equations as Wiener functionals and apply to them some infinite dimensional functional analysis. This idea was due to P. Malliavin.
(9911 views)
Markov Chains and Stochastic Stabilityby S.P. Meyn, R.L. Tweedie - Springer
The book on the theory of general state space Markov chains, and its application to time series analysis, operations research and systems and control theory. An advanced graduate text and a monograph treating the stability of Markov chains.
(21990 views)
Applied Stochastic Processes in Science and Engineeringby Matt Scott - University of Waterloo
This book is designed as an introduction to the ideas and methods used to formulate mathematical models of physical processes in terms of random functions. A senior undergraduate course offered to students with a suitably mathematical background.
(7974 views)
Stochastic Differential Equations: Models and Numericsby Anders Szepessy, et al. - KTH
The goal of this course is to give useful understanding for solving problems formulated by stochastic differential equations models in science, engineering and finance. Typically, these problems require numerical methods to obtain a solution.
(7642 views)