You could compute the cross correlation at 0 lag using r = xcorr(___,scaleopt) where scaleopt can be set to a normalization option.
If you're looking for the cross correlation coefficient, use R = corrcoef(A,B)
Demo:
sig1 = 1./(1+exp(-5:5));
sig2 = 1./(1+exp(-6:4));
plot(sig1);
hold on
plot(sig2);
rm = corrcoef(sig1, sig2); % Column vectors
r2 = rm(2)
r1 = xcorr(sig1, sig2, 0)
r1norm = xcorr(sig1, sig2, 0, 'normalized')
The difference is that corrcoef subtracts the mean from each vector and then normalizes the vectors to be unit vectors whereas xcorr with 'normalized' only normalizes but does not subtract the mean.
r1centered = xcorr(sig1-mean(sig1), sig2-mean(sig2), 0, 'normalized')
