It is shown that, in a hierarchically structured hypotheses space, any belief function whose focal elements are nodes in the hierarchy is a separable support function. An algorithm is proposed that decomposes such a separable support function into simple support functions. It is shown that the computational complexity of this decomposition algorithm is O(N/sup 2/). Applications of the decomposition of separable support functions to the data fusion problem and the reasoning about control problem are discussed.
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