Semi-parametric classification of noisy curves

摘要

We propose a novel semi-parametric modeling strategy for classifying noisy curves. This strategy uses a family of non-linear parametric models to describe known aspects of the signal and its propagation, with a non-parametric component incorporating unmodeled characteristics. We propose a novel multi-record model building strategy and assess its scope in classifying acoustic and radar signals. Our experiments suggest that the semi-parametric approach generally out performs the parametric approach, and in certain circumstance gives better performance than the non-parametric approach. In all cases, it is close to the best approach considered, with the added advantage of interpretable coefficients in the parametric component.