[Eeglablist] Some questions about runica.m function of EEGLAB
Seyed Mohammad Reza Shahshahni
smr.shahshahani at gmail.com
Sat Sep 5 01:55:45 PDT 2015
Dear all
Looking at the code in the "runica.m" function of EEGLAB, I couldn't
understand some parts.
1- Why is the data broken into blocks and what is the basis for the size of
those blocks?
2- The learning rule is different from the reference papers.
weights = weights + lrate*(BI+(1-2*y)*u')*weights;
In the papers there is I, not BI. Why has the identity matrix been
multiplied by B?
3- In the sphering or decorrelation of the data, why is cov^(-0.5)
multiplied by 2?
4- What is the role of bias term?
5- What is the Annealing for?
6- How should the covariance matrix be normalized? By N or N-1 ?
Thanks
S. M. R. Shahshahani
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