I need to process 72 hours of sampling at a rate of 25.6 kHz. The MatLab files I am given have the form of a structure, with string fields containing instrument information, units, etc. The numerical data itself is contained in 262144x2 double fields named StreamSegment000000_000255, StreamSegment000256_000511, and so forth, each of which containing 10.24 seconds of data. The file I am currently working on has roughly 2 hours of data, divided into 703 10.24-second fields of size 262144x2 double and a 2.84-second field of size 72704x2 double (of course, files will have different sizes). The first thing I need to compute is 30-second RMS for all 72 hours. Here is my approach:
Now cell2mat(C) will of course lead me "??? Error using ==> cat; Out of memory", so I tried to break down to several matrices.
eval(sprintf('M%d = cell2mat(C((1+3*(i-1)):(3*i),:));', i));
If number=235, obtaining 235 matrices each containing 3 of these 10.24-second fields would allow me to easily compute 30.72-second rms (close enough) for these 2 hours. Of course, this works just fine for small "numbers", but I quickly encounter "*??? Error using ==> cat Out of memory" again.
I could try nested for-loops and progressively clear out the memory, but I am sure there are solutions that are a lot more elegant and efficient.