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Circular Cross Covariance

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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/fil...bjectId=1093734

Reference:
A. V. Oppenheim, R. W. Schafer and J. R. Buck, Discrete-Time Signal Processing, Upper Saddler River, NJ : Prentice Hall, 1999.

Free download from Shareware Connection - CXCOV Circular Cross Covariance function estimates

Publisher: G. Levin | License: Shareware
Version: 1.0 | Size: 10 KB | Platform: Matlab, Scripts
Released Date: 21-05-2013 | Rating: 0 | Title: Circular Cross Covariance

Author Url: http://www.mathworks.com/
Program Info Url: http://www.mathworks.com/
Download Url: http://www.mathworks.com/matlabcentral/fx_files/4811/1/cxcov.zip

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Circular Cross Correlation - CXCORR Circular Cross Correlation function estimates

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Circular Cross Covariance keywords:
Circular Cross Covariance related downloads:

Circular Cross Correlation - CXCORR Circular Cross Correlation function estimates

Fast Circular (Periodic) Cross Correlation - Uses fft to calculate the circular cross correlation of two periodic signal vectors.

Joint Frequency and Delay Correlation - Performs an efficient circular cross correlation between two vectors over all possible frequency offsets (Dopplers) between -pi and pi where 2pi is the sampling rate

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