Go to main content

PDF

Description

Iterated random functions are used to draw pictures or simulate large Ising models, among other applications. Random iterations offer a method for studying the steady state distribution of a Markov chain, and give useful bounds on rates of convergence in a variety of examples. The present paper surveys the field and presents some new examples. There is a simple unifying idea: the iterates of random Lipschitz functions converge if the functions are contracting on the average.

Details

Files

Statistics

from
to
Export
Download Full History
Formats
Format
BibTeX
MARCXML
TextMARC
MARC
DublinCore
EndNote
NLM
RefWorks
RIS