A comparison study of polynomial-based PCA, KPCA, LDA and GDA feature extraction methods for epileptic and eye states EEG signals detection using kernel machines

Nkengfack, Laurent Chanel Djoufack; Tchiotsop, Daniel; Atangana, Romain; Tchinda, Beaudelaire Saha; Louis-Door, Valérie

doi:10.1016/j.imu.2021.100721

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A comparison study of polynomial-based PCA, KPCA, LDA and GDA feature extraction methods for epileptic and eye states EEG signals detection using kernel machines

Cited by 9 publications

References 27 publications

An Empirical Study on Comparison of Machine Learning Algorithms for Eye-State Classification Using EEG Data

An Empirical Study on Comparison of Machine Learning Algorithms for Eye-State Classification Using EEG Data

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