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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Veröffentlicht in:	2018 3rd International Conference on Intelligent Green Building and Smart Grid (IGBSG) S. 1 - 4
Hauptverfasser:	Ge, Sunan, Yang, Yan, Ni, Wei, Zhang, Rui
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 01.04.2018
Schlagworte:	Brain modeling Correlation coefficient EEG Electroencephalography Electrooculography Mathematical model ocular artifacts Principal component analysis Tensile stress tensor underdermined blind source separation
Online-Zugang:	Volltext
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