 If data generated by a random vector "X" are observed as vectors "X"i of observations with covariance matrix Σ, a linear transformation can be used to decorrelate the data.To do this, the Cholesky decomposition is used to express Σ = "A" "A"'.Then the transformed vector "Y"i = "A"−1"X"i has the identity matrix as its covariance matrix.