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Removal of noise can be done in various ways: Conventional filters: You could create a digital low-pass filter, such as a Chebyshev or Butterworth filter with a cut-off frequency at 30 Hz (filt or filtfilt function in Matlab). FFT-based filtering: FIR filters remove frequencies in the frequency domain. So first a Fourier transform is done and then the ...


2

This article by Bobrov et. al seems to be similar to what you are looking for. They were able to classify (at above chance performance) whether subjects were imagining houses or faces. The training protocol is particularly interesting: they started by showing subjects pictures, but then used a feedback process of showing the subjects the output of the ...


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The field of study you should focus on is the one for which you have already identified in your paragraph above which is EEG based "brain-computer interface". EEG signals are compared by their "features". Each of the signal you have provided above have different features. These features can be mean, variance, frequency, kurtosis, skewness of each of the ...



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