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say there is a number of arrays with length 12, containing signed integers in a range of roughly ±100, how can i compare the 'signature' or 'harmonic content' of these arrays to each other, in a way that is more accurate than a simple weighted average?

Would i have to look into neural networks (if this even would be suitable, i don't know tbh) or is there a more straightforward way?

EDIT:

on a graph, imagine the index on the x-axis and the value on the y-axis. two arrays would be very similar if the shape of the graphs would be similar after normalization.

i find it hard to find the right words for this problem.

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  • Define "more accurate". "Mean distance" is as good as anything else when you have no clue what sort of "similarity" you're talking about. Commented Jan 22, 2010 at 1:34
  • Are you trying to do pitch detection? Commented Jan 22, 2010 at 1:44
  • code.google.com/p/echo-nest-java-api i'm using this API for musical analysis and try to process the timbre information. Commented Jan 22, 2010 at 1:53

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The arrays could be treated as signals, hence you should try to do a scaled cross correlation between the two signals, or extract frequency domain info and compare their spectrum ( FFT of both signals ).

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