We introduce a signal processing model for signals in non-white noise, where the exact noise spectrum is a priori unknown. The model is based on a Student's t distribution and constitutes a natural generalization of the widely used normal (Gaussian) model. This way, it allows for uncertainty in the noise spectrum, or more generally is also able to accommodate outliers (heavy-tailed noise) in the data. Examples are given pertaining to data from gravitational wave detectors.
@article{arxiv.0804.3853,
title = {Modelling coloured residual noise in gravitational-wave signal processing},
author = {Christian Röver and Renate Meyer and Nelson Christensen},
journal= {arXiv preprint arXiv:0804.3853},
year = {2015}
}