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Retrieving a Context Tree from EEG Data

1
Instituto de Matemática e Estatística, Universidade de São Paulo, São Paulo 05508-090, Brazil
2
Centro de Matemática, Universidad de la República, Uruguay and Instituto Pasteur de Montevideo, Montevideo 11400, Uruguay
3
Instituto de Matemática, Universidade Federal do Rio de Janeiro, Rio de Janeiro 21941-909, Brazil
4
Instituto de Biofísica, Universidade Federal do Rio de Janeiro, Rio de Janeiro 21941-902, Brazil
*
Author to whom correspondence should be addressed.
Mathematics 2019, 7(5), 427; https://doi.org/10.3390/math7050427
Received: 28 March 2019 / Revised: 30 April 2019 / Accepted: 5 May 2019 / Published: 14 May 2019
(This article belongs to the Special Issue Stochastic Processes in Neuronal Modeling)
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Abstract

It has been repeatedly conjectured that the brain retrieves statistical regularities from stimuli. Here, we present a new statistical approach allowing to address this conjecture. This approach is based on a new class of stochastic processes, namely, sequences of random objects driven by chains with memory of variable length. View Full-Text
Keywords: stochastic chains with memory of variable length; sequences of random objects driven by context tree models; stochastic modeling of EEG data stochastic chains with memory of variable length; sequences of random objects driven by context tree models; stochastic modeling of EEG data
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Duarte, A.; Fraiman, R.; Galves, A.; Ost, G.; Vargas, C.D. Retrieving a Context Tree from EEG Data. Mathematics 2019, 7, 427.

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