# MATLAB: How to compute the similarity of two signals and get the correct consistency or coherence metric

I was wondering about the consistency metric. Generally, it allows us to deduce the parity or similarity between two signals, right? If so, if the probability is higher (from 0.5 to 1), does it means that there is a strong similarity of the signals? If the margin is less than (0.1-0.43), can this predict the poor coherence between the signals (or poor similarity, the probability the signals are different)? So, if we got the metric <0, is this approved the signal is totally different? Because I'm getting negative numbers. Is this hypothesis possible?

Can I have a clear understanding of the consistency metric of the signal? Here is my small code. Thanks in advance.

s1 = signal3
s2 = signal4

if  s1 ~= s2
[C1] = xcorr(s1);
[C2] = xcorr(s2);
signal_mix = C1.*C2   %mixing vector
signal_mix1 = signal_mix
else
s1(1,:) == s2(1,:)
s3 = s1
s3= s2
signal_mix = s2
end

n =2;

for i = length(signal_mix1)
signal_mix1(i) = min(C1(i),C2(i))/ max(C1(i),C2(i)) % consistency score
signal_mix2 = sum(signal_mix1(i))
end 