Classification for dynamical systems: model-based and data-driven approaches

We address the problem of classifying trajectories generated by dynamical systems. We consider the model-based approach, which is the classic approach in control theory, and (data-driven) 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. Examples are given to substantiate the analysis.