Covariance to correlation matrix
[cor,sd] = CL_cov2cor(cov)
Computes the correlation matrix and the standard deviations vector from the covariance matrix.
The correlation matrix and standard deviation vector are built as follows:
- cor(i,i) = 1
- cor(i,j) = cov(i,j) / (sd(i) * sd(j))
- sd(i) = cov(i,i)^(1/2)
Covariance matrix (NxNxK)
Correlation matrix (NxNxK)
Standard deviations vectors (NxK)
CNES - DCT/SB
// Random covariance matrix : N=6; K=2; mat = rand(N,N,K,key="normal"); cov = mat'*mat; // symetrical [cor,sd] = CL_cov2cor(cov); // Retrieving the covariance : cov2 = CL_cor2cov(cor,sd) ; | ![]() | ![]() |