The design and implementation of multi-character classification scheme based on EEG signals of visual imagery-Reference-Cited by-同舟云学术

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The design and implementation of multi-character classification scheme based on EEG signals of visual imagery

Published:2024-03-09 Issue: Volume: Page:
ISSN:1871-4080
Container-title:Cognitive Neurodynamics
language:en
Short-container-title:Cogn Neurodyn

Author:

Pan Hongguang^ORCID,Song Wei,Li Li,Qin Xuebin

Funder

National Natural Science Foundation of China

Xi’an Science and Technology Program

Qin Chuangyuan “Scientists + Engineers”Team Construction Program in Shaanxi Province

Natural Science Basic Research Program of Shaanxi Province

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s11571-024-10087-z.pdf

Reference42 articles.

1. Alom KM, Islam S (2020) Classification for the P300-based brain computer interface (BCI). In: 2020 2nd international conference on advanced information and communication technology (ICAICT), pp. 387–391

2. Altan A, Karasu S (2020) Recognition of COVID-19 disease from X-ray images by hybrid model consisting of 2D curvelet transform, chaotic salp swarm algorithm and deep learning technique. Chaos Solit Fract 140:110071

3. Babo RM, Buot A, Tallon BC (2019) Neural responses to heartbeats distinguish self from other during imagination. NeuroImage 191:10–20

4. Bang JS, Jeong JH, Won DO (2021) Classification of visual perception and imagery based EEG signals using convolutional neural networks. In: 2021 9th international winter conference on brain-computer interface (BCI), pp. 1–6

5. Boashash B (2015) Time-frequency signal analysis and processing: a comprehensive reference

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