Design of a robust fusion of probability densities

The paper deals with the fusion of probability densities. A selection of the weights of the weighted geometric mean of densities is justified, as well as the selection of the geometric mean itself, from a more general perspective. It is shown that the Chernoff fusion provides the density that minimises the greatest Kullback-Leibler divergence to the densities that are being fused. The interpretation of the densities is discussed and finally, illustrative examples are provided.