In the past I've used auto-correlation to detect periodic structures in numeric data. This algorithm works even if the data isn't repeated (exact copies) but just follows a general periodic structure. It can also work okay if the data is binary, e.g. I've used it to detect rhythm patterns and metric structure in music. But what algorithm can I use to do the same with non-numeric data e.g. a sequence of symbols? It seems like if you replaced the multiplication of values with a lookup through a similarity matrix you could essentially use auto-correlation on non-numeric data, but I don't think you'd be able to do it fast with FFT. Is there a better algorithm?
Auto-correlation-like algorithm for detecting periods in non-numeric data?
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