[Eeglablist] ICA runs slowly and returns complex numbers

[Arnaud Delorme]

Dear Ilana,

did your ICA solution converge (meaning that the weight difference decrease with time). This might be the issue.
Also, are you using average reference or linked mastoid. In this case, the data matrix rank is the number of channels minus 1. ICA tries to detect this automatically but sometimes fails. You then have to manually reduce the number of dimension by 1 when running ICA. If you have 64 channels, in the edit box for running ICA (where there is already 'extended', 1) you may add 'pca', 63.

Best,

Arno

On Nov 12, 2013, at 11:54 PM, Ilana Podlipsky <ilana.mlist at gmail.com> wrote:

> Hi All,
> 
> Since I've recently changed my computer ICA in eeglab runs very very slowly and returns complex numbers.
> On my previous computer, on the same data I ran the same ICA  within an hour or two. On the new computer the same ICA takes more than 24 hours, After 512 steps it returns this message :
> 
> Sorting components in descending order of mean projected variance ...
> Warning: Matrix is close to singular or badly scaled.
>          Results may be inaccurate. RCOND = 6.956943e-019.
> 
> When I try to plot the ICA activations I don't see any traces and when I look into the EEG.icaact matrix I see only complex numbers. Tried both runica and binica. 
> This has never happen to me with the old computer on the same dataset.
> Both the old and new computer run Win7 64bit, matlab 2008a and eeglab 12. The hardware of the computers is different.
> 
> What could be the reason for this, and what can ?I do to solve this?
> 
> Thanks for the help,
> Ilana
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