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Evidence Supporting Measure Of Similarity For Reducing The Complexity In Information Fusion, Florentin Smarandache, Jean Dezert, Xinde Li, Xinhan Huang

Branch Mathematics and Statistics Faculty and Staff Publications

This paper presents a new method for reducing the number of sources of evidence to combine in order to reduce the complexity of the fusion processing. Such a complexity reduction is often required in many applications where the real-time constraint and limited computing resources are of prime importance. The basic idea consists in selecting, among all sources available, only a subset of sources of evidence to combine. The selection is based on an evidence supporting measure of similarity (ESMS) criterion which is an efficient generic tool for outlier sources identification and rejection. The ESMS between two sources of evidence can …