Open Access. Powered by Scholars. Published by Universities.®
Physical Sciences and Mathematics Commons™
Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 3 of 3
Full-Text Articles in Physical Sciences and Mathematics
Uniform And Partially Uniform Redistribution Rules, Florentin Smarandache, Jean Dezert
Uniform And Partially Uniform Redistribution Rules, Florentin Smarandache, Jean Dezert
Branch Mathematics and Statistics Faculty and Staff Publications
This short paper introduces two new fusion rules for combining quantitative basic belief assignments. These rules although very simple have not been proposed in literature so far and could serve as useful alternatives because of their low computation cost with respect to the recent advanced Proportional Conflict Redistribution rules developed in the DSmT framework.
Evidence Supporting Measure Of Similarity For Reducing The Complexity In Information Fusion, Florentin Smarandache, Jean Dezert, Xinde Li, Xinhan Huang
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 …
Evidence Supporting Measure Of Similarity For Reducing The Complexity In Information Fusion, Xinde Li, Jean Dezert, Florentin Smarandache, Xinhan Huang
Evidence Supporting Measure Of Similarity For Reducing The Complexity In Information Fusion, Xinde Li, Jean Dezert, Florentin Smarandache, Xinhan Huang
Branch Mathematics and Statistics Faculty and Staff Publications
This paper proposes a new solution for reducing the number of sources of evidence to be combined in order to diminish the complexity of the fusion process required in some applications where the real-time constraint and strong computing resource limitation are of prime importance. The basic idea consists in selecting, among the whole set of sources of evidence, only the biggest subset of sources which are not too contradicting based on a criterion of Evidence Supporting Measure of Similarity (ESMS) in order to process solely the coherent information received. The ESMS criterion serves actually as a generic tool for outlier …