Long Short-Term Memory Employed for Classifying P300-Based BCI-Reference-Cited by-同舟云学术

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Long Short-Term Memory Employed for Classifying P300-Based BCI

Published:2024-05-19 Issue: Volume:346 Page:666-671
ISSN:
Container-title:2024 IEEE 4th International Maghreb Meeting of the Conference on Sciences and Techniques of Automatic Control and Computer Engineering (MI-STA)
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Author:

Aljlaly Ahlam M¹,Elshami Ibtihal Fawzi²,Almijbari Ahmed³

Affiliation:

1. Bright Star University,Electrical and Electronics Engineering Department,Brega,Libya

2. College of Electrical and Electronics Technology,Electronics Engineering Department,Benghazi,Libya

3. Technical University of Munich,The Neuroimaging Center,Munich,Germany

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10599605/10599569/10599751.pdf?arnumber=10599751

Reference15 articles.

1. Riemann-Based Algorithms Assessment for Single- and Multiple-Trial P300 Classification in Non-Optimal Environments

2. Introduction to neural networks;Cross;The Lancet,1995

3. Past, Present, and Future of EEG-Based BCI Applications

4. A Hybrid Asynchronous Brain-Computer Interface Combining SSVEP and EOG Signals

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