@article{EJP538,
author = {Pierre Collet and Antonio Galves and Florencia Leonardi},
title = {Random perturbations of stochastic processes with unbounded variable length memory},
journal = {Electron. J. Probab.},
fjournal = {Electronic Journal of Probability},
volume = {13},
year = {2008},
keywords = {chains of infinite order, variable length Markov chains, chains with unbounded variable length memory, random perturbations, algorithm Context, context trees.},
abstract = {We consider binary infinite order stochastic chains perturbed by a random noise. This means that at each time step, the value assumed by the chain can be randomly and independently flipped with a small fixed probability. We show that the transition probabilities of the perturbed chain are uniformly close to the corresponding transition probabilities of the original chain. As a consequence, in the case of stochastic chains with unbounded but otherwise finite variable length memory, we show that it is possible to recover the context tree of the original chain, using a suitable version of the algorithm Context, provided that the noise is small enough.},
pages = {no. 48, 1345-1361},
issn = {1083-6489},
doi = {10.1214/EJP.v13-538},
url = {http://ejp.ejpecp.org/article/view/538}}