# Calculate similarity between two time series using discrete wavelet transform cofficients

I am new to the field of signal processing but I have read that DWT can be used to find similarity between two time series, I am curious as to what kind of similarity measure do we use once we have calculated the the approx and detailed coefficients for both the time series at an appropriate decomposition level.

So for example using DWT on time series1 I will have an array which contains :

[12,10,4.5,7,-2.8,-1.2]

Similarly for second time series I will have:

[17,9,8,23,-3,-6.8]


Now what similarity measure do i use to find a similarity index.

I am coding in Python, if that helps.