Circular Cross Covariance

Circular Cross Covariance function estimate.

CXCOV Circular Cross Covariance function estimates.
CXCOV(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]=CXCOV(a,b) returns the length M-1 circular cross covariance sequence c with corresponding lags x.

The circular cross covariance is the normalized circular cross correlation function of two vectors with their means removed:
c(k) = sum[a(n)-mean(a))*conj(b(n+k)-mean(b))]/[norm(a-mean(a))*norm(b-mean(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 correlation between a and b look for CXCORR(a,b) in
http://www.mathworks.com/matlabcentral/fileexchange/loadAuthor.do?objectType=author&objectId=1093734

Reference:
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.