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Random perturbations of stochastic processes with unbounded variable length memory

  
@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}}