A Hamiltonian-based algorithm for measurements clustering
Daniele Casagrande, Alessandro Astolfi · 2008
The paper describes a novel method for clustering points in the plane. The proposed algorithm is based on the notions of clustering function and level lines; the clusters are identified as the level sets corresponding to a reference value of the clustering function. The core idea is to regard the clustering function as a Hamiltonian function and to determine the level lines as the trajectories of the associated Hamiltonian system. The method is illustrated on two practical problems.