These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

152 related articles for article (PubMed ID: 26736755)

  • 1. Spatial filter and feature selection optimization based on EA for multi-channel EEG.
    Wang Y; Mohanarangam K; Mallipeddi R; Veluvolu KC
    Annu Int Conf IEEE Eng Med Biol Soc; 2015; 2015():2311-4. PubMed ID: 26736755
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Time-frequency analysis of band-limited EEG with BMFLC and Kalman filter for BCI applications.
    Wang Y; Veluvolu KC; Lee M
    J Neuroeng Rehabil; 2013 Nov; 10():109. PubMed ID: 24274109
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Evolutionary Algorithm Based Feature Optimization for Multi-Channel EEG Classification.
    Wang Y; Veluvolu KC
    Front Neurosci; 2017; 11():28. PubMed ID: 28203141
    [TBL] [Abstract][Full Text] [Related]  

  • 4. 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]  

  • 5. A PCA aided cross-covariance scheme for discriminative feature extraction from EEG signals.
    Zarei R; He J; Siuly S; Zhang Y
    Comput Methods Programs Biomed; 2017 Jul; 146():47-57. PubMed ID: 28688489
    [TBL] [Abstract][Full Text] [Related]  

  • 6. 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]  

  • 7. 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]  

  • 8. 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]  

  • 9. Multi-View Multi-Scale Optimization of Feature Representation for EEG Classification Improvement.
    Jiao Y; Zhou T; Yao L; Zhou G; Wang X; Zhang Y
    IEEE Trans Neural Syst Rehabil Eng; 2020 Dec; 28(12):2589-2597. PubMed ID: 33245696
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Enhancing the Hybrid BCI Performance With the Common Frequency Pattern in Dual-Channel EEG.
    Ko LW; Komarov O; Lin SC
    IEEE Trans Neural Syst Rehabil Eng; 2019 Jul; 27(7):1360-1369. PubMed ID: 31180893
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Efficient Classification of Motor Imagery Electroencephalography Signals Using Deep Learning Methods.
    Majidov I; Whangbo T
    Sensors (Basel); 2019 Apr; 19(7):. PubMed ID: 30978978
    [TBL] [Abstract][Full Text] [Related]  

  • 12. An embedded implementation based on adaptive filter bank for brain-computer interface systems.
    Belwafi K; Romain O; Gannouni S; Ghaffari F; Djemal R; Ouni B
    J Neurosci Methods; 2018 Jul; 305():1-16. PubMed ID: 29738806
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Major Depression Detection from EEG Signals Using Kernel Eigen-Filter-Bank Common Spatial Patterns.
    Liao SC; Wu CT; Huang HC; Cheng WT; Liu YH
    Sensors (Basel); 2017 Jun; 17(6):. PubMed ID: 28613237
    [TBL] [Abstract][Full Text] [Related]  

  • 14. The backtracking search optimization algorithm for frequency band and time segment selection in motor imagery-based brain-computer interfaces.
    Wei Z; Wei Q
    J Integr Neurosci; 2016 Sep; 15(3):347-364. PubMed ID: 27681162
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Relevant Feature Selection from a Combination of Spectral-Temporal and Spatial Features for Classification of Motor Imagery EEG.
    Kirar JS; Agrawal RK
    J Med Syst; 2018 Mar; 42(5):78. PubMed ID: 29546648
    [TBL] [Abstract][Full Text] [Related]  

  • 16. RSTFC: A Novel Algorithm for Spatio-Temporal Filtering and Classification of Single-Trial EEG.
    Qi F; Li Y; Wu W
    IEEE Trans Neural Netw Learn Syst; 2015 Dec; 26(12):3070-82. PubMed ID: 25730834
    [TBL] [Abstract][Full Text] [Related]  

  • 17. 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]  

  • 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. Modified CC-LR algorithm with three diverse feature sets for motor imagery tasks classification in EEG based brain-computer interface.
    Siuly ; Li Y; Paul Wen P
    Comput Methods Programs Biomed; 2014 Mar; 113(3):767-80. PubMed ID: 24440135
    [TBL] [Abstract][Full Text] [Related]  

  • 20. A functional source separation algorithm to enhance error-related potentials monitoring in noninvasive brain-computer interface.
    Ferracuti F; Casadei V; Marcantoni I; Iarlori S; Burattini L; Monteriù A; Porcaro C
    Comput Methods Programs Biomed; 2020 Jul; 191():105419. PubMed ID: 32151908
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 8.