A Validity Measure for Fuzzy Clustering
IEEE Transactions on Pattern Analysis and Machine Intelligence
A survey of moment-based techniques for unoccluded object representation and recognition
CVGIP: Graphical Models and Image Processing
System identification (2nd ed.): theory for the user
System identification (2nd ed.): theory for the user
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
On cluster validity for the fuzzy c-means model
IEEE Transactions on Fuzzy Systems
Brief paper: Observer design for range and orientation identification
Automatica (Journal of IFAC)
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A method to estimate the dynamics of clusters is presented. An existing static clustering method, which makes use of a Hamiltonian function, is exploited in the dynamic case, when the points to cluster do not remain in fixed positions but move with unknown dynamics. The time is discretised and the static algorithm is applied to each time-instant. While identifying each cluster, the algorithm also performs the computation of the moments of the cluster. By estimating the dynamics of the moments an approximate estimation of the dynamics of the cluster is obtained. An illustrative example shows the performance of the method.