MATLAB: Do “corr(x,y)” and “xcorr(x,y)” give different answers when x and y are simulated discrete samples of radar signals of form a*e^ib, with partially correlated randomized b values

MATLABsignal correlations

To calculate the correlation between discrete samples from two simulated radar signals (column vectors of equal length), there appear to be two approaches in Matlab. One is the function "corr(x,y)" in the statistics toolbox and the other is "xcorr(x,y)" in the signal processing toolbox. For a given set of signal samples x,y these two functions give different results and the reason for the difference is not apparent.

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It would be helpful if you could provide a script showcasing the difference and explain why you think the two should be the same.

From the documentation, corr and xcorr are quite different. corr computes the correlation coefficients between the two sequences, while xcorr computes the correlation of one sequence with another sequence at different delays. So to me it's expected that the two results are different.

HTH

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MATLAB: Corr(x,y) nan

I think you are looking for corrcoef instead of corr. To exclude the nan values, use

a = [78 88 87 54 68 91 72 nan 88 nan];
b = [nan 35 42 44 67 55 nan 34 25 33];
r = corrcoef(a,b, 'rows','complete')

MATLAB: Why the result of cross-correlation coefficient is 1

Hi Bin, the Cyclist is absolutely right. There is no difference between the two because all you have done is invert the wavelet transform.

When you say there are differences, what are the sizes of these "differences"?

execute this line and see what you get:

    max(abs(x-y))

I get something on the order of 10^(-12) for my particular realization of randn().

When the largest difference between any two elements of a vector is that small, then you should not expect the cross correlation sequence to be anything but 1 at all lags.

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MATLAB: Corr(x,y) nan

MATLAB: Why the result of cross-correlation coefficient is 1

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