Hello everybody,
I have 3500 mat files that contain a 128*4408 matrix each (128 is the dimension and 4408 is the number of features), and I have to reduce the dimensionality of the features by PCA (from 128 to 64, for example).
To do this, I append all the 3500 matrices to obtain a 128*15428000 matrix X (15428000 = 3500*4408) and then use
[~, Xnew] = pcares(X,64);
for PCA reconstruction.
The problem is, the amount of memory needed to store X and Xnew is about 128*15428000*8 bytes ~ 15Gb each, while I only have 4Gb of RAM.
Could anybody please suggest me a way to overcome this problem?
I tried to use VVAR but did not really understand how it works. I tried first to create a 10000*10000 matrix:
vvar.createFile(10000*10000);x=vvar(10000,10000);
but got the following error:
Error using vvar (line 251)The file created by "vvar.createFile(N)" has insufficient space left
Thank you in advance for your help.
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