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Since the groundbreaking work of the Kalman filter in the 1960s, considerable effort has been devoted to discrete time filters for dynamic state estimation, especially including a variety of suboptimal implementations of the Bayesian filter. The essence of the Bayesian filter is to make the (sub)optimum fusion of the observation information in time sequence based on the hidden Markov model of the...
In this paper, we consider a special multi-source data clustering problem for which the data-points from the same source cannot be grouped into the same cluster, namely cannot link (CL) constraint, and the sizes of the generated clusters are subject to maximum thresholds. No prior information is given about the level of clutter (namely noisy data) or the number of clusters. Particularly, the clusters...
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