Multiple ocular artifacts removal based on high-order statistical tensor algorithm

The aim of this paper is to propose a multiple ocular artifacts (OAs) removal method using the high order tensor algorithm. Four categories high order tensor methods are adopted to separate the real electroencephalogram (EEG) and ocular signals by underdetermined blind source separation (UBSS) model...

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Vydané v:	2018 3rd International Conference on Intelligent Green Building and Smart Grid (IGBSG) s. 1 - 4
Hlavní autori:	Ge, Sunan, Yang, Yan, Ni, Wei, Zhang, Rui
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 01.04.2018
Predmet:	Brain modeling Correlation coefficient EEG Electroencephalography Electrooculography Mathematical model ocular artifacts Principal component analysis Tensile stress tensor underdermined blind source separation
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