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From: Delta V on 17 Jun 2010 21:52
I have two sets of data from an event. A was sampled at 1KHz while B was sampled at 400Hz.

I want to create C which is A sampled at 400Hz. How do utilize B to help create C so that B and C correlate as closely as possible?

I need to overlay B and C visually and compute % error at each sample point. Guys I'm trying to be as descriptive as possible while trying to narrow the scope of my question. Have an odd feeling, I haven't mastered the balance but am working on it.


Thank you for looking.
Cheers
DeltaV
From: ImageAnalyst on 17 Jun 2010 22:30
Do you have time stamps for each sample? It looks like you're going
to have to interpolate a new sample every 2.5 samples of A to create
C, but where C(1) starts, I don't know. Should C(1) start at A(1), or
at A(2), or somewhere else? If there are time stamps, do they have to
align to give you the best correlation?

Maybe you should upsample B to 1 kHz and then to a cross correlation
to find the optimal shift, and then interpolate A to get C once you
know the shift.
From: ImageAnalyst on 17 Jun 2010 22:47
Sorry - that should say "...then do a cross correlation ..." with
xcorr().
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