**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

**Introduction to Stochastic Processes**

by

**Gordan Žitković**-

**The University of Texas at Austin**

Contents: Probability review; Mathematica in 15 minutes; Stochastic Processes; Simple random walk; Generating functions; Random walks - advanced methods; Branching processes; Markov Chains; The 'Stochastics' package; Classification of States; etc.

(

**7977**views)

**Advanced Stochastic Processes**

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.

(

**8005**views)

**Lectures on Singular Stochastic PDEs**

by

**M. Gubinelli, N. Perkowski**-

**arXiv**

The aim is to introduce the basic problems of non-linear PDEs with stochastic and irregular terms. We explain how it is possible to handle them using two main techniques: the notion of energy solutions and that of paracontrolled distributions.

(

**6678**views)

**Stochastic Differential Equations: Models and Numerics**

by

**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.

(

**7918**views)