Answers are grounded in this paper and cite their sources.
Abstract 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.
No takes yet. Share an insight, caveat, or question.
Röver et al. (2010) studied this question.
Synapse has enriched 10 related papers. Consider them for comparative context: