Nonparametric Identification of Linear Time-Varying Systems using Gaussian Process Regression. Issue 2 (2020) - Hallemans, N.; Lataire, J.; Pintelon, R.
Abstract: Linear time-varying systems are a class of systems, the dynamics of which evolve in time. This results in a time-varying frequency response function where each frequency has a time-varying gain. In classical identification techniques, basis functions are employed to fit these time-varying gains. In this paper a new method based on Gaussian process regression is presented. The advantage of the proposed method is a more convenient model structure and model order selection.