Gaussian process regression Repeating each measurement multiple times is not practical at scale. Alternatively, by applying a Gaussian process regression (GPR) in a sliding window across the impedance vector, an estimate for the noise level could be achieved from just one measurement. GPR can be defined as an ordinary Bayesian regression with an infinite dimensional parameter space of unknown nonlinear regression functions . It is based on a Gaussian process, which is a stochastic process parameterized by two functions. Firstly, its mean function