[1] |
刘琳琳,陈健,李松,等. 基于相位同步与AR的运动想象脑电信号特征提取研究[J]. 软件导刊, 2018,17(3):7-10.
|
[2] |
王行愚,金晶,张宇,等. 脑控:基于脑-机接口的人机融合控制[J]. 自动化学报, 2013,39(3):208-221.
|
[3] |
唐建友. 结合脑电信息的多自由度肌电假手研究[D]. 杭州:杭州电子科技大学, 2009.
|
[4] |
NOURMOHAMMADI A, JAFARI M, ZANDER T O. A survey on unmanned aerial vehicle remote control using brain-computer interface[J]. IEEE Transactions on Human-Machine Systems, 2018,48(4):337-348.
|
[5] |
WANG H T, LI T, BEZERIANOS A, et al. The control of a virtual automatic car based on multiple patterns of motor imagery BCI[J]. Medical & Biological Engineering & Computing, 2019,57(1):299-309.
|
[6] |
LIU Y L, SU W B, LI Z J, et al. Motor-imagery-based teleoperation of a dual-arm robot performing manipulation tasks[J]. IEEE Transactions on Cognitive and Developmental Systems, 2019,11(3):414-424.
|
[7] |
IQBAL H, AQIL M. A QR decomposition based RLS algorithm with forgetting factor for adaptation of AR EEG features[C]// Proceedings of the 2016 International Conference on Emerging Technologies. 2016. DOI: 10.1109/ICET.2016.7813250.
|
[8] |
ANG K K, CHIN Z Y, ZHANG H H, et al. Filter bank common spatial pattern (FBCSP) in brain-computer interface[C]// Proceedings of the 2008 IEEE International Joint Conference on Neural Networks. 2008:2390-2397.
|
[9] |
RAMOSER H, MULLER-GERKING J, PFURTSCHELLE
|
|
R G. Optimal spatial filtering of single trial EEG during imagined hand movement[J]. IEEE Transactions on Rehabilitation Engineering, 2000,8(4):441-446.
|
[10] |
GAUR P, GUPTA H, CHOWDHURY A, et al. A sliding window common spatial pattern for enhancing motor imagery classification in EEG-BCI[J]. IEEE Transactions on Instrumentation and Measurement, 2021,70. DOI:10.1109
|
|
/TIM.2021.3051996.
|
[11] |
ZHENG W F, XU F Z, SHU M L, et al. Classification of motor imagery electrocorticogram signals for brain-computer interface[C]// Proceedings of the 2019 9th International IEEE/EMBS Conference on Neural Engineering (NER). 2019:530-533.
|
[12] |
SINGH V P, KUMAR P. Naive Bayes classifier for word sense disambiguation of Punjabi language[J]. Malaysian Journal of Computer Science, 2018,31(3):188-199.
|
[13] |
KUMAR S, SHARMA A, MAMUN K, et al. A deep learning approach for motor imagery EEG signal classification[C]// Proceedings of the 2016 3rd Asia-Pacific World Congress on Computer Science and Engineering (APWC on CSE). 2016:34-39.
|
[14] |
DE J, ZHANG X W, LIN F, et al. Transduction on directed graphs via absorbing random walks[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2018,40(7):1770-1784.
|
[15] |
MA J T, LIN F, WESARG S, et al. A novel Bayesian model incorporating deep neural network and statistical shape model for pancreas segmentation[C]// Proceedings of the 2018 International Conference on Medical Image Computing and Computer-Assisted Intervention. 2018:480-487.
|
[16] |
唐贤伦,李伟,马伟昌,等. 基于条件经验模式分解和串并行CNN的脑电信号识别[J]. 电子与信息学报, 2020,42(4):1041-1048.
|
[17] |
杨涛,马玉良,高云园,等. 基于增强卷积神经网络模型的运动想象脑电信号识别方法[J]. 航天医学与医学工程, 2021,34(2):128-136.
|
[18] |
宋春宁,盛勇,宁正高. 基于深度学习的运动想象脑电信号识别方法[J]. 传感器与微系统, 2022,41(4):125-128.
|
[19] |
WANG Q L, WU B G, ZHU P F, et al. ECA-Net: Efficient channel attention for deep convolutional neural networks[C]// Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 2020:11531-11539.
|
[20] |
BLANKERTZ B, MULLER K R, CURIO G, et al. The BCI competition 2003: Progress and perspectives in detection and discrimination of EEG single trials[J]. IEEE Transactions on Biomedical Engineering, 2004,51(6):1044-1051.
|
[21] |
陈浩滨,葛薇,杨超,等. 脑电波信号多域变换与深度学习癫痫诊断[J]. 现代信息科技, 2022,6(20):6-10.
|
[22] |
GROBBELAAR M, PHADIKAR S, GHADERPOUR E, et al. A survey on denoising techniques of electroencephalogram signals using wavelet transform[J]. Signals, 2022,3(3):577-586.
|
[23] |
王天宇,陈晗,王刚,等. 采用小波变换和双向长短期记忆网络的脑电睡眠分期模型[J]. 西安交通大学学报, 2022,56(9):104-111.
|
[24] |
XU K, BA J, KIROS R, et al. Show, attend and tell: Neural image caption generation with visual attention[C]// Proceedings of the 32nd International Conference on Machine Learning. 2015:2048-2057.
|
[25] |
钱嘉鑫,余鹏飞,李海燕,等. 基于特征融合与注意力的野生菌细粒度分类[J/OL]. 激光与光电子学进展,2023,60(04):100-109.
|
[26] |
LECUN Y, BOTTOU L, BENGIO Y, et al. Gradient-based learning applied to document recognition[J]. Proceedings of the IEEE, 1998,86(11):2278-2324.
|
[27] |
罗飞,刘鹏飞,罗元,等. 多特征融合的运动想象脑电特征提取方法[J]. 计算机应用, 2020,40(2):616-620.
|
[28] |
陈锋. 基于运动想象的脑-机接口系统分类方法研究[D]. 郑州:郑州大学, 2020.
|
[29] |
杨怀花,叶庆卫,罗慧艳,等. 改进孪生网络的脑电信号处理方法[J]. 计算机测量与控制, 2022,30(3):211-216.
|