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… Click to show full abstract
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.
               
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