Semi-parametric signal analysis

We propose a modelling strategy for signals corrupted by additive noise. This combines a nonlinear parametric model to encapsulate domain knowledge, and a nonparametric component to extract further structure. Models of this type exploit the flexibility of nonparametric techniques without sacrificing physical interpretability. We propose a model building strategy based on grey box ideas (Bohlin and Grabe, 1995) and show how our approach can be used to classify signals. To illustrate our approach we consider a radar target classification example