EEG-based imagined words classification using Hilbert transform and deep networks
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Hardware and Architecture,Media Technology,Software
Link
https://link.springer.com/content/pdf/10.1007/s11042-023-15664-8.pdf
Reference46 articles.
1. Agarwal P, Kumar S (2021) Transforming Imagined Thoughts into Speech Using a Covariance-Based Subset Selection Method. Indian J Pure Appl Phys
2. 59:180-3. http://nopr.niscair.res.in/handle/123456789/56517. Accessed 5 Jan 2022
3. Agarwal P, Kumar S (2022) Electroencephalography based imagined alphabets classification using spatial and time-domain features. Int J Imaging Syst Technol 32:111–122. https://doi.org/10.1002/ima.22655
4. Asghari Bejestani MR, Mohammad Khani GhR, Nafisi VR, Darakeh F (2022) EEG-Based Multiword Imagined Speech Classification for Persian Words. BioMed Res Int 2022:8333084. https://doi.org/10.1155/2022/8333084
5. Bakhshali MA, Khademi M, Ebrahimi-Moghadam A, Moghimi S (2020) EEG signal classification of imagined speech based on Riemannian distance of correntropy spectral density. Biomed Signal Process Control 59:101899. https://doi.org/10.1016/j.bspc.2020.101899
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