pbashivan / EEGLearn

A set of functions for supervised feature learning/classification of mental states from EEG based on "EEG images" idea.

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About the average power in your file "FeatureMat_time"

haojiubujian91 opened this issue · comments

Dear professor:
In your file "FeatureMat_time", The maximum value of the feature is 51.65, the minimum is -1.05, and the mean value is 0.0017.
But after the FFT using np.fft.fft, the power value is generally between 0 and 100. Therefore, for these features, did you normalize them or log them? I don’t know your specific operation, I hope you can give some specific code about this part.

In addition, about the frequency band, I set the theta (4-7 Hz), alpha (7-13 Hz) and beta (13-30 Hz). But in your experiment, you did not specify the range of these bands. Did you choose the same as mine?

Looking forward to your reply, thank you very much

The window size I use is 15s. Therefore, after the FFT using the np.fft.fft, the power values is between 0-50445, this number is a bit too large, so I want to ask how you deal with these power values, normalization or log?

@haojiubujian91 hello,i have same problem,could share your wechat for further communication,my wechat:19821234051

features are all normalized within frequency bands. It usually helps with the training of neural networks if your features are normalized.

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@haojiubujian91 I also have the same problem, can I get your wechat for some communication,my wechat 18749845267