Summary
The Gaussian process latent force model (GPLFM) has been shown to be an effective and practical method for a number of tasks within dynamics, for example, joint estimation of inputs and states or, more recently, in the recovery of nonlinear restoring forces for system identification. One possible limitation of the GPLFM is that the estimated force is modelled a priori as a Gaussian process, hence is a stationary process. This work extends the model to account for non-stationary force estimation, whether an external or internal forcing, by means of a deep GPLFM formulation.
