2023
DOI: 10.3390/electronics12122743
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Deep Comparisons of Neural Networks from the EEGNet Family

Abstract: A preponderance of brain–computer interface (BCI) publications proposing artificial neural networks for motor imagery (MI) electroencephalography (EEG) signal classification utilize one of the BCI Competition datasets. However, these databases encompass MI EEG data from a limited number of subjects, typically less than or equal to 10. Furthermore, the algorithms usually include only bandpass filtering as a means of reducing noise and increasing signal quality. In this study, we conducted a comparative analysis… Show more

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Cited by 9 publications
(1 citation statement)
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“…By synchronization with examining hierarchical structures in industry, benefits society [48]. The use of biosignals in optimizing and controlling industrial operations is critical [49], as is the programming for ML-based data acquisition in industrial operations and management systems constants [50]; [51]. Paired mathematical modeling provides a solid basis for exploring algorithmics for quality management but not without horizontal integration of the physics of security constants.…”
Section: Adopting Am Principles From Aviation Industrymentioning
confidence: 99%
“…By synchronization with examining hierarchical structures in industry, benefits society [48]. The use of biosignals in optimizing and controlling industrial operations is critical [49], as is the programming for ML-based data acquisition in industrial operations and management systems constants [50]; [51]. Paired mathematical modeling provides a solid basis for exploring algorithmics for quality management but not without horizontal integration of the physics of security constants.…”
Section: Adopting Am Principles From Aviation Industrymentioning
confidence: 99%