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In this work, we propose a novel way to approximating mixtures of Gaussian distributions by a set of deter-ministically chosen Dirac delta components. This approximation is performed by adapting a method for approximating single Gaussian distributions to the considered case. The proposed method turns the approximation problem into an optimization problem by minimizing a distance measure between the...
In multi-sensor distributed estimation fusion, local estimation errors are correlated in general. Two extreme ways to handle this correlation is either to ignore them completely or to have them fully considered. There is another case in the middle: it admits the existence of the correlation, but does not know how large it is. A sensible way is to set up an optimality criterion and optimize it over...
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