Normalized deep learning algorithms based information aggregation functions to classify motor imagery EEG signal-Reference-Cited by-同舟云学术

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Normalized deep learning algorithms based information aggregation functions to classify motor imagery EEG signal

Published:2023-08-16 Issue:30 Volume:35 Page:22725-22736
ISSN:0941-0643
Container-title:Neural Computing and Applications
language:en
Short-container-title:Neural Comput & Applic

Author:

Al-Hamadani Ammar A.^ORCID,Mohammed Mamoun J.,Tariq Suphian M.

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Software

Link

https://link.springer.com/content/pdf/10.1007/s00521-023-08944-9.pdf

Reference40 articles.

1. Graimann B, Allison B, Pfurtscheller G (2010) Brain–computer interfaces: A gentle introduction. In: Graimann B, Pfurtscheller G, Allison B (eds) Brain–computer interfaces. Springer, Berlin, pp 1–27

2. Klaes C (2018) Invasive brain–computer interfaces and neural recordings from humans. Handb Behav Neurosci 28(2014):527–539

3. Luis F, Moncayo G (2017) Niedermeyer’s electroencephalography, vol 1. Oxford University Press, Oxford

4. Tariq M, Uhlenberg L, Trivailo P, Munir KS, Simic M (2017) Mu-beta rhythm ERD/ERS quantification for foot motor execution and imagery tasks in BCI applications. In: 2017 8th IEEE international conference on cognitive infocommunications (CogInfoCom), pp 000091–000096

5. Budiman WY, Tjandrasa H, Navastara DA (2016) Classification of EEG signals using common spatial pattern-principle component analysis and interval type-2 fuzzy logic system. In: 2016 international conference on information and communication technology and systems (ICTS), pp 85–89

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Self-supervised motor imagery EEG recognition model based on 1-D MTCNN-LSTM network;Journal of Neural Engineering;2024-05-17

2. Hybrid Deep Learning Based PDOA Model for Prediction of BCI Task Using EEG Signals;2023 International Conference on Ambient Intelligence, Knowledge Informatics and Industrial Electronics (AIKIIE);2023-11-02

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