EEG signals classification using the K-means clustering and a multilayer perceptron neural network model

By Umut Orhan, Mahmut Hekim, Mahmut Ozer. Expert systems with applications, 2011

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EEG based multi-class seizure type classification using convolutional neural network and transfer learning (2020, methodology): “In the second method, we have applied k-means clustering using city block distance metric for the same DWT based features as reported in El-Menshawy, Benharref, and Serhani (2015) and Orhan, Hekim, and Ozer (2011).”
Feature extraction and classification for EEG signals using wavelet transform and machine learning techniques (2015, methodology): “depending on the principal frequency components in the given signal [2].”