Even more generally, p(y | x) ∝ exp(-Tr((X - μ) T .σ-1.(X - μ))), where μ is the mean value of X. Suppose R is the variance-covariance matrix when a Gaussian noise component is assumed and Y is the matrix corresponding to the measurements y. The R-norm is defined as follows:
