EEG signal classification for BCI applications by wavelets and interval type-2 fuzzy logic systems
Propose Haar wavelet transformation and ROC curve for EEG signal feature extraction. Combine wavelets and interval type-2 fuzzy logic system for EEG signal classification. Benchmark datasets downloaded from the BCI competition II are used for experiments. Proposed wavelet-IT2FLS outperforms the winner methods of the BCI competition II. IT2FLS dominates competing classifiers: FFNN, SVM, kNN, AdaBoost and ANFIS.
eeg signal classification interval type-2 fuzzy logic system wavelet transformation bci competition ii receiver operating characteristics (roc) curve