4.6 Review

Gaussian Processes for Signal Processing and Representation in Control Engineering

Journal

APPLIED SCIENCES-BASEL
Volume 12, Issue 10, Pages -

Publisher

MDPI
DOI: 10.3390/app12104946

Keywords

Gaussian process; control engineering; signal processing; practical applications; optimization; modelling

Funding

  1. AGH's Research University Excellence Initiative
  2. Polish National Science Centre project Process Fault Prediction and Detection [UMO-2021/41/B/ST7/03851]

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Gaussian processes are flexible stochastic processes that can model complex functions and have broad applications in various fields of automation.
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.

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