running Person's correlation

[Francesco Potortì]

Hi all,

I have a signal (long) and a template (short, fixed).  I have to compute
the Pearson's correlation of the short signal with a sliding window of
the long signal.  This is a convolution where each sample is divided by
the (fixed) standard deviation of the short signal and the running
standard deviation of the long signal.

The only loopless way I can think of is to compute a running sum, a
running sum of squares, and use them to compute a running standard
deviation to be multiplied with the convolution.  Any more
straightforward methods?

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