[Eeglablist] Using PCA before ICA decomposition? (Chang Gu)

[stauros dimitriadis]

Dear Chang
Since it is important to reduce the dimensionality of your data by adopting PCA, a simple rule is to select 
an appropriate number of principal components regarding the variance of your data.

In MATLAB script:
[pc,score,latent,tsquare] = princomp( (time x triasl)  x channel); % concatenate your trials in time (suggested)
r=find(cumsum(latent)./sum(latent) > 0.98);
%r(1) is the total number of components need to capture more than 98 % of the variance of 
%your initial data

Afterward, proceed with the ICA.

I hope that i help you !!



Best regards
Stavros Dimitriadis
http://users.auth.gr/~stdimitr/index.html 

1)Electronics Laboratory, Department of Physics, University of Patras
2)Artificial Intelligence Information Analysis lab Department of Informatics
Aristotle University of Thessaloniki
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