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