Reversibility and Stochastic Networks
by F.P. Kelly
Publisher: John Wiley and Sons Ltd 1979
Number of pages: 233
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.
Home page url
Download or read it online for free here:
by 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.
by 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.
by Jan A. Van Casteren - Bookboon
In this book, which is basically self-contained, the following topics are treated thoroughly: Brownian motion as a Gaussian process, Brownian motion as a Markov process, Brownian motion as a martingale, Markov chains, renewal theory, etc.
by H. Kunita - Tata Institute Of Fundamental Research
The author presents basic properties of stochastic flows, specially of Brownian flows and their relations with local characteristics and with stochastic differential equations. Various limit theorems for stochastic flows are presented.