Using Exponential Mixture Models for Suboptimal Distributed Data Fusion

Abstract

In this paper we investigate the use of Exponential Mixture Densities (EMDs) as suboptimal update rules for distributed data fusion. We show that EMDs have a pointwise bound "from below" on the minimum value of the probability distribution. However, the distributions are not bounded from above and thus can be interpreted as a fusion operation.