I have installed R-2.8.1 right now and will proceed with my tests. So
far I haven't used it.
The fault is presumably caused by a sort of misuse of the memory on my
part.
The attached R script (whose last Step is not debugged yet) implements
the algorithm for signal features extraction described in the attached
paper. Needless to say, to get good statistics we need plenty of
data.Therefore I started out with a minimum of 30 signals (please find
attached 48 detrended, denoised, centralized, standardized, and
compressed signals I am using with the script). The algorithm generates
many big matrices and vectors. Roughly a matrix is generated at each
step. Of course in my last script version
I will remove the useless data structures dynamically. At the time
being, though, I keep them all because I have to trace back each data
elaboration step.
Between successive runs I clear the console but rarely I clear the
workspace. Even if the data structures are generated again at each run,
maybe the system memory stack gets fragmented ? ... just my worthless
guess ...
I am afraid I cannot  prune the code without changing the algorithm. The
detected fault seems to be a memory problem. Therefore, the allocation
of big data structures over and over again is suspicious ...

About the algorithm... my implementation seems to perform according to
the prescription. However, I am not enthusiastic with results depending
on vague choices of the parameters. Basically the number of signal
features extracted depends on an arbitrary input threshold. Maybe
someone in the R-help list might suggest a better, more robust, way to
extract features from mono-channel signals ...

Kind regards,
   Maura E
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