844 related articles for article (PubMed ID: 28161876)
1. A spatial-frequency-temporal optimized feature sparse representation-based classification method for motor imagery EEG pattern recognition.
Miao M; Wang A; Liu F
Med Biol Eng Comput; 2017 Sep; 55(9):1589-1603. PubMed ID: 28161876
[TBL] [Abstract][Full Text] [Related]
2. Optimizing spatial patterns with sparse filter bands for motor-imagery based brain-computer interface.
Zhang Y; Zhou G; Jin J; Wang X; Cichocki A
J Neurosci Methods; 2015 Nov; 255():85-91. PubMed ID: 26277421
[TBL] [Abstract][Full Text] [Related]
3. Temporally Constrained Sparse Group Spatial Patterns for Motor Imagery BCI.
Zhang Y; Nam CS; Zhou G; Jin J; Wang X; Cichocki A
IEEE Trans Cybern; 2019 Sep; 49(9):3322-3332. PubMed ID: 29994667
[TBL] [Abstract][Full Text] [Related]
4. CSP-TSM: Optimizing the performance of Riemannian tangent space mapping using common spatial pattern for MI-BCI.
Kumar S; Mamun K; Sharma A
Comput Biol Med; 2017 Dec; 91():231-242. PubMed ID: 29100117
[TBL] [Abstract][Full Text] [Related]
5. Discriminative spatial-frequency-temporal feature extraction and classification of motor imagery EEG: An sparse regression and Weighted Naïve Bayesian Classifier-based approach.
Miao M; Zeng H; Wang A; Zhao C; Liu F
J Neurosci Methods; 2017 Feb; 278():13-24. PubMed ID: 28012854
[TBL] [Abstract][Full Text] [Related]
6. A new parameter tuning approach for enhanced motor imagery EEG signal classification.
Kumar S; Sharma A
Med Biol Eng Comput; 2018 Oct; 56(10):1861-1874. PubMed ID: 29616456
[TBL] [Abstract][Full Text] [Related]
7. Class discrepancy-guided sub-band filter-based common spatial pattern for motor imagery classification.
Luo J; Wang J; Xu R; Xu K
J Neurosci Methods; 2019 Jul; 323():98-107. PubMed ID: 31141703
[TBL] [Abstract][Full Text] [Related]
8. Sparse Representation-Based Extreme Learning Machine for Motor Imagery EEG Classification.
She Q; Chen K; Ma Y; Nguyen T; Zhang Y
Comput Intell Neurosci; 2018; 2018():9593682. PubMed ID: 30510569
[TBL] [Abstract][Full Text] [Related]
9. Sparse Bayesian Learning for Obtaining Sparsity of EEG Frequency Bands Based Feature Vectors in Motor Imagery Classification.
Zhang Y; Wang Y; Jin J; Wang X
Int J Neural Syst; 2017 Mar; 27(2):1650032. PubMed ID: 27377661
[TBL] [Abstract][Full Text] [Related]
10. A new discriminative common spatial pattern method for motor imagery brain-computer interfaces.
Thomas KP; Guan C; Lau CT; Vinod AP; Ang KK
IEEE Trans Biomed Eng; 2009 Nov; 56(11 Pt 2):2730-3. PubMed ID: 19605314
[TBL] [Abstract][Full Text] [Related]
11. Sparse representation-based classification scheme for motor imagery-based brain-computer interface systems.
Shin Y; Lee S; Lee J; Lee HN
J Neural Eng; 2012 Oct; 9(5):056002. PubMed ID: 22872668
[TBL] [Abstract][Full Text] [Related]
12. Classification of multi-class motor imagery with a novel hierarchical SVM algorithm for brain-computer interfaces.
Dong E; Li C; Li L; Du S; Belkacem AN; Chen C
Med Biol Eng Comput; 2017 Oct; 55(10):1809-1818. PubMed ID: 28238175
[TBL] [Abstract][Full Text] [Related]
13. The CSP-Based New Features Plus Non-Convex Log Sparse Feature Selection for Motor Imagery EEG Classification.
Zhang S; Zhu Z; Zhang B; Feng B; Yu T; Li Z
Sensors (Basel); 2020 Aug; 20(17):. PubMed ID: 32842635
[TBL] [Abstract][Full Text] [Related]
14. Uncorrelated multiway discriminant analysis for motor imagery EEG classification.
Liu Y; Zhao Q; Zhang L
Int J Neural Syst; 2015 Jun; 25(4):1550013. PubMed ID: 25986750
[TBL] [Abstract][Full Text] [Related]
15. An improved discriminative filter bank selection approach for motor imagery EEG signal classification using mutual information.
Kumar S; Sharma A; Tsunoda T
BMC Bioinformatics; 2017 Dec; 18(Suppl 16):545. PubMed ID: 29297303
[TBL] [Abstract][Full Text] [Related]
16. Improvement motor imagery EEG classification based on sparse common spatial pattern and regularized discriminant analysis.
Fu R; Han M; Tian Y; Shi P
J Neurosci Methods; 2020 Sep; 343():108833. PubMed ID: 32619588
[TBL] [Abstract][Full Text] [Related]
17. Spatial-Frequency Feature Learning and Classification of Motor Imagery EEG Based on Deep Convolution Neural Network.
Miao M; Hu W; Yin H; Zhang K
Comput Math Methods Med; 2020; 2020():1981728. PubMed ID: 32765639
[TBL] [Abstract][Full Text] [Related]
18. Feature selection using regularized neighbourhood component analysis to enhance the classification performance of motor imagery signals.
Malan NS; Sharma S
Comput Biol Med; 2019 Apr; 107():118-126. PubMed ID: 30802693
[TBL] [Abstract][Full Text] [Related]
19. Frequency-Optimized Local Region Common Spatial Pattern Approach for Motor Imagery Classification.
Park Y; Chung W
IEEE Trans Neural Syst Rehabil Eng; 2019 Jul; 27(7):1378-1388. PubMed ID: 31199263
[TBL] [Abstract][Full Text] [Related]
20. Learning Optimal Time-Frequency-Spatial Features by the CiSSA-CSP Method for Motor Imagery EEG Classification.
Hu H; Pu Z; Li H; Liu Z; Wang P
Sensors (Basel); 2022 Nov; 22(21):. PubMed ID: 36366225
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
