Jun 1, 2015 · This paper introduces an approach to classify motor imagery EEG signals using an interval type-2 fuzzy logic system (IT2FLS) in a combination with wavelet ...
Jul 13, 2019 · This paper introduces an approach to classify motor imagery EEG signals using an interval type-2 fuzzy logic system (IT2FLS) in a combination ...
This paper introduces an approach to classify motor imagery EEG signals using an interval type-2 fuzzy logic system (IT2FLS) in a combination with wavelet ...
This paper introduces an approach to classify motor imagery EEG signals using an interval type-2 fuzzy logic system (IT2FLS) in a combination with wavelet ...
This paper introduces an approach to classify motor imagery EEG signals using an interval type-2 fuzzy logic system (IT2FLS) in a combination with wavelet ...
EEG signal clas- sification for BCI applications by wavelets and interval type-2 fuzzy logic systems. Expert Systems with Applications, 42(9), pp.4370-4380.
Bibliographic details on EEG signal classification for BCI applications by wavelets and interval type-2 fuzzy logic systems.
This paper proposes an EEG signal translation system based on motoric imagery activities that includes band-pass filter and Common Spatial Pattern for noise ...
The T2 fuzzy classifier has been proven to outperform its type-1 (T1) counterpart on all data sets recorded from three subjects examined and has also ...
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This paper introduces a method to classify EEG signals using features extracted by an integration of wavelet transform and the nonparametric Wilcoxon test.