CXCORR Circular Cross Correlation function estimates.
CXCORR(a,b), where a and b represent samples taken over time interval T which is assumed to be a common period of two corresponding periodic signals.
a and b are supposed to be length M row vectors, either real or complex.
[x,c]=CXCORR(a,b) returns the length M-1 circular cross correlation sequence c with corresponding lags x.
The circular cross correlation is:
c(k) = sum[a(n)*conj(b(n+k))]/[norm(a)*norm(b)];
where vector b is shifted CIRCULARLY by k samples.
The function doesn't check the format of input vectors a and b!
For circular covariance between a and b look for CXCOV(a,b) in
A. V. Oppenheim, R. W. Schafer and J. R. Buck, Discrete-Time Signal Processing, Upper Saddler River, NJ : Prentice Hall, 1999.
Author: G. Levin, April 2004.
G. Levin (2021). Circular Cross Correlation (https://www.mathworks.com/matlabcentral/fileexchange/4810-circular-cross-correlation), MATLAB Central File Exchange. Retrieved .
How can I apply this code to find circular cross correlation between two images
Notice that you cycle b backwards, b(2) becomes b(1), while in cross-correlation the shift should be forwards - b(1) become b(1+1)=b(2). This might be because different conventions of definitions of cross-correlation. I use the one in Wikipedia:
(a star b)[n] = sum_k( a*[k] b[k+n] ).
Otherwise, nice code.
I'm also wondering why the mean of a and b are not subtracted. Please let me know if you can explain.
If i want to use zadoff chu sequence is anyone knows how i can make it. if i donot want to use ltezadoffchu command
why are you take the values (25,29,34) in zadoff sequenc(lte)
I'm sorry, but I don't understand how it works too (about the means of a and b) can you give an example, please..
my mistake ! ignore the preceding comment !
I'm surprised it is not working only for me.. I get that :
??? In an assignment A(I) = B, the number of elements in B and
I must be the same.
Error in ==> cxcorr at 30
.. what's is happening ?
How come the mean of a and b are not subtracted before divided by norm? I'm assuming the result is a normalized norm , please corect me if I'm wrong.
Very useful for my term project, thanks.
Excellent, this is exactly what i was looking for!!! Ive been trying to correlate optical field profiles and this is the best tool that ive found
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