  We consider the problem of classifying trajectories generated by dynamical
systems. We investigate a model-based approach, the common approach in control
engineering, and a data-driven approach based on Support Vector Machines, a
popular method in the area of machine learning. The analysis points out
connections between the two approaches and their relative merits.
