Gaussian Processes for Signal Processing and Representation in Control Engineering
Adrian Dudek, Jerzy Baranowski
Abstract
The Gaussian process is an increasingly well-known type of stochastic process, which is a generalization of the Gaussian probability distribution. It allows us to model complex functions thanks to its flexibility, which would not be possible with the use of other tools. Gaussian processes also have a couple of other features that are used in various branches of automation with positive results, ranging from industrial processes to image processing. There are also many ways of setting up the Gaussian processes, which required knowledge on the topic and depend on the presented problem. Considerations on these topics lead to the conclusion that the current state of practical usefulness of Gaussian processes increases significantly, therefore the deepening of knowledge about the ways of its use is highly suggested. In this review, we present selected technical applications of Gaussian Processes allowing an understanding of their broad applicability.