Three-class classification of motor imagery EEG data including “rest state” using filter-bank multi-class Common Spatial pattern-Reference-Cited by-同舟云学术

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Three-class classification of motor imagery EEG data including “rest state” using filter-bank multi-class Common Spatial pattern

Published:2015-01 Issue: Volume: Page:
ISSN:
Container-title:The 3rd International Winter Conference on Brain-Computer Interface
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Author:

Shiratori T.,Tsubakida H.,Ishiyama A.,Ono Y.

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/7063652/7073013/07073053.pdf?arnumber=7073053

Cited by 11 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. IMH-Net: a convolutional neural network for end-to-end EEG motor imagery classification;Computer Methods in Biomechanics and Biomedical Engineering;2023-11-07

2. Real-Time Motor Imagery-Based Brain–Computer Interface System by Implementing a Frequency Band Selection;Arabian Journal for Science and Engineering;2023-06-20

3. Imagined Speech Classification Using EEG and Deep Learning;Bioengineering;2023-05-26

4. Low-Cost Brain-Computer Interface Design Using Deep Learning for Internet of Brain Controlled Things Applications;2022 International Conference on Computational Science and Computational Intelligence (CSCI);2022-12

5. EEG Classifier Using Wavelet Scattering Transform-Based Features and Deep Learning for Wheelchair Steering;2022 International Conference on Computational Science and Computational Intelligence (CSCI);2022-12

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