Qingguo Wei

发表

Independent Component Analysis for Spatial Filtering and Feature Extraction in a Four-Task Brain-Computer Interface

Qingguo Wei, Yuhui Ma, Zongwu Lu, 2010, 2010 Second International Conference on Intelligent Human-Machine Systems and Cybernetics.

Channel Extension Uniting Information Theoretic Feature Extraction Based Multiclass Common Spatial Pattern Used in BCI

Qingguo Wei, Yuanqin Chen, 2014 .

Binary particle swarm optimization for frequency band selection in motor imagery based brain-computer interfaces.

Qingguo Wei, Zhonghai Wei, Qingguo Wei, 2015, Bio-medical materials and engineering.

Transfer Learning Based on Regularized Common Spatial Patterns Using Cosine Similarities of Spatial Filters for Motor-Imagery BCI

Hua Zhang, Jing Hua, Qingguo Wei, 2019, J. Circuits Syst. Comput..

VEP-based brain-computer interfaces modulated by Golay complementary series for improving performance.

Yin Huang, Qingguo Wei, Zongwu Lu, 2016, Technology and health care : official journal of the European Society for Engineering and Medicine.

A Training Data-Driven Canonical Correlation Analysis Algorithm for Designing Spatial Filters to Enhance Performance of SSVEP-Based BCIs

Yijun Wang, Hai Guo, Xuan Wu, 2020, Int. J. Neural Syst..

An Unweighted Exhaustive Diagonalization Based Multi-Class Common Spatial Pattern Algorithm in Brain-Computer Interfaces

Yuhui Ma, Qingguo Wei, Kui Chen, 2010, 2010 2nd International Conference on Information Engineering and Computer Science.

Channel Selection for Optimizing Feature Extraction in an Electrocorticogram-Based Brain-Computer Interface

Yuhui Ma, Qingguo Wei, Zongwu Lu, 2010, Journal of clinical neurophysiology : official publication of the American Electroencephalographic Society.

Channel selection by genetic algorithms for classifying single-trial ECoG during motor imagery

Qingguo Wei, Wei Tu, Qingguo Wei, 2008, 2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

Classification of EEG Signals Based on Filter Bank and Sparse Representation in Motor Imagery Brain-Computer Interfaces

Jin Wang, Qingguo Wei, Jin Wang, 2020, J. Circuits Syst. Comput..

A Comparative Study of Canonical Correlation Analysis and Power Spectral Density Analysis for SSVEP Detection

Qingguo Wei, Zongwu Lu, Meixia Xiao, 2011, 2011 Third International Conference on Intelligent Human-Machine Systems and Cybernetics.

Classification of Three-Class Motor Imagery EEG Data by Combining Wavelet Packet Decomposition and Common Spatial Pattern

Wei Tu, Qingguo Wei, 2009, 2009 International Conference on Intelligent Human-Machine Systems and Cybernetics.

Data from: A multi-target brain-computer based on code modulated visual evoked potentials

Qingguo Wei, Zongwu Lu, Yonghui Lui, 2019 .

Joint selection of time and frequency segments for classifying multiclass EEG data in motor imagery based BCIs

Qingguo Wei, Renxiang Han, 2015, 2015 12th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD).

Stimulus Specificity of Brain-Computer Interfaces Based on Code Modulation Visual Evoked Potentials

Siwei Feng, Qingguo Wei, Zongwu Lu, 2016, PloS one.

Electrode channel selection based on backtracking search optimization in motor imagery brain-computer interfaces.

Qingguo Wei, Shengfa Dai, 2017, Journal of integrative neuroscience.

A multi-target brain-computer interface based on code modulated visual evoked potentials

Qingguo Wei, Zongwu Lu, Yonghui Liu, 2018, PloS one.

Extension of common spatial pattern (CSP) algorithm to multi-task case by Jacobi Rotations for single-trial EEG classification

Lin Liu, Qingguo Wei, 2009, 2009 4th International IEEE/EMBS Conference on Neural Engineering.

Binary multi-objective particle swarm optimization for channel selection in motor imagery based brain-computer interfaces

Qingguo Wei, Yanmei Wang, Qingguo Wei, 2011, 2011 4th International Conference on Biomedical Engineering and Informatics (BMEI).

The backtracking search optimization algorithm for frequency band and time segment selection in motor imagery-based brain-computer interfaces.

Qingguo Wei, Zhonghai Wei, Qingguo Wei, 2016, Journal of integrative neuroscience.

Grouping modulation with different codes for improving performance in cVEP-based brain–computer interfaces

Qingguo Wei, Zongwu Lu, Huayun Gong, 2017 .

Transfer Learning Based on Hybrid Riemannian and Euclidean Space Data Alignment and Subject Selection in Brain-Computer Interfaces

Yan Li, Qingguo Wei, Yuebin Chen, 2021, IEEE Access.

Application of quadratic optimization to multi-class common spatial pattern algorithm in brain-computer interfaces

Yuhui Ma, Qingguo Wei, Kui Chen, 2010, 2010 3rd International Conference on Biomedical Engineering and Informatics.

Amplitude and phase coupling measures for feature extraction in an EEG-based brain–computer interface

Yijun Wang, Xiaorong Gao, Shangkai Gao, 2007, Journal of neural engineering.

Maximum Signal Fraction Analysis for Enhancing Signal-to-Noise Ratio of EEG Signals in SSVEP-Based BCIs

Shan Zhu, Xiaorong Gao, Xuan Wu, 2019, IEEE Access.

Channel Reduction by Cultural-Based Multi-objective Particle Swarm Optimization Based on Filter Bank in Brain–Computer Interfaces

Qingguo Wei, Zongwu Lu, Yanmei Wang, 2014 .

Wavelet packet coefficients weighted for frequency optimization in motor imagery based brain-computer interfaces

Qingguo Wei, Bin Wan, 2011, 2011 4th International Conference on Biomedical Engineering and Informatics (BMEI).

Feature Extraction and Subset Selection for Classifying Single-Trial ECoG during Motor Imagery

Xiaorong Gao, Shangkai Gao, Qingguo Wei, 2006, 2006 International Conference of the IEEE Engineering in Medicine and Biology Society.

Optimal Frequency Band Selection Based on Filter Banks and Wavelet Packet Decomposition in Multi-class Brain–Computer Interfaces

Qingguo Wei, Zongwu Lu, Bin Wan, 2014 .

A Novel c-VEP BCI Paradigm for Increasing the Number of Stimulus Targets Based on Grouping Modulation With Different Codes

Yijun Wang, Xiaorong Gao, Chen Yang, 2018, IEEE Transactions on Neural Systems and Rehabilitation Engineering.