On a family of fuzzy measures for data fusion with reduced complexity

Choquet integrals are one of the appropriate methods for fusing numerical information. They aggregate numerical values with respect to a fuzzy measure, a way to represent importance that is an alternative to the weights in a weighted mean. The use of fuzzy measures, although extremely flexible when compared with weighting vectors, presents some difficulties when used in real applications: to define a fuzzy measure to combine n values, 2/sup n/-2 parameters have to be settled. In this paper, we present a family of fuzzy measures with reduced complexity and we show that they are either adequate for redundant information sources or complementary ones.