Since noise is not uniform across the whole EIS spectrum , Equation is extended with a weight matrix B to account for frequency-dependent variations of the noise. In the simplest case without cross-correlation of noise between different frequencies, B is a diagonal matrix containing the inverse of the noise standard deviation of the data vector Z. It is used to weight the data and, accordingly, the kernel . Then the residual term in Equation becomes