The PCA diagonalizes the maximum likelihood estimate of the covariance matrix
$ C=\frac{1}{n} \sum_{i=1}^{n} \vec{x_i}{x_i}^T $
by solving the eigenvalue equation
$ C\vec{x} = \lambda \vec{x} $
The PCA diagonalizes the maximum likelihood estimate of the covariance matrix
$ C=\frac{1}{n} \sum_{i=1}^{n} \vec{x_i}{x_i}^T $
by solving the eigenvalue equation
$ C\vec{x} = \lambda \vec{x} $