Modelling and Inference using Locally Stationary Processes : Biomedical applications
This thesis considers statistical methods for non-stationary signals, specifically stochastic modelling, inference on the model parameters and optimal spectral estimation. The models are based on Silverman’s definition of Locally Stationary Processes (LSPs). In all the contributions, an example of a biomedical application of the proposed method is provided. In the first two papers, the methods are
