Nonlinear signal classification using geometric statistical features in state space

A new methodology in the framework of high-dimensional shape analysis in state space is proposed for nonlinear signal classification. The zero-crossing rate on a Poincare surface of a section is used as a feature. Experiments regarding oceanic signal classification show that the proposed methodology can provide some information not contained in spectra.