MATLAB: Why we extract feature of eeg signal for network neural? (energy, energy power density, convariance, entropy)

analysis eeg signal

I read more thesis for analysis eeg, but i dont understand why must extract feature, every one can explain detail (energy, energy power density, convariance, entropy). Please!

what do i find documents for this thesis? you can share documents?

thank everyone! ——————————————— you can send to my mail: anhoa1013063@gmail.com

Best Answer

Feature extraction allows models to concentrate on the characteristics of the input data that are the most correlated with the desired output. Too much input data that has no output predicting qualities acts as noise and foils the ability to obtain good results

Hope this helps.

Thank you for formally accepting my answer

Greg

Related Solutions

MATLAB: How to implement neural network for eeg motor imagery classification

If you have c classes, the target columns should be columns of the c-dimension unit matrix eye(c).

 [ I N ]  = size(input) % [ 16 140 ]
 [ c N ] = size(target)  % [c  140 ]

For classification tutorials and examples search BOTH the NEWSREADER and ANSWERS with

 greg patternnet

For documentation and associated unsatisfactory examples:

 help patternnet
 doc patternnet