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- DSmT (4)
- Information fusion (4)
- Belief functions (2)
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- Bayes rule (1)
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- Belief function (1)
- Complexity reduction (1)
- Conditioning (1)
- DST (1)
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- Importance (1)
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- Neutrosophic logic (1)
- PCR5 fusion rules (1)
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- Reliability (1)
- Robot perception (1)
- Uniform redistribution rule; partially uniform redistribution rule; belief functions; Dezert-Smarandache Theory (DSmT); information fusion (1)
Articles 1 - 6 of 6
Full-Text Articles in Other Mathematics
Importance Of Sources Using The Repeated Fusion Method And The Proportional Conflict Redistribution Rules #5 And #6, Florentin Smarandache, Jean Dezert
Importance Of Sources Using The Repeated Fusion Method And The Proportional Conflict Redistribution Rules #5 And #6, Florentin Smarandache, Jean Dezert
Branch Mathematics and Statistics Faculty and Staff Publications
We present in this paper some examples of how to compute by hand the PCR5 fusion rule for three sources, so the reader will better understand its mechanism. We also take into consideration the importance of sources, which is different from the classical discounting of sources.
Extended Pcr Rules For Dynamic Frames, Florentin Smarandache, Jean Dezert
Extended Pcr Rules For Dynamic Frames, Florentin Smarandache, Jean Dezert
Branch Mathematics and Statistics Faculty and Staff Publications
In most of classical fusion problems modeled from belief functions, the frame of discernment is considered as static. This means that the set of elements in the frame and the underlying integrity constraints of the frame are fixed forever and they do not change with time. In some applications, like in target tracking for example, the use of such invariant frame is not very appropriate because it can truly change with time. So it is necessary to adapt the Proportional Conflict Redistribution fusion rules (PCR5 and PCR6) for working with dynamical frames. In this paper, we propose an extension of …
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 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, 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 …
Non Bayesian Conditioning And Deconditioning, Jean Dezert, Florentin Smarandache
Non Bayesian Conditioning And Deconditioning, Jean Dezert, Florentin Smarandache
Branch Mathematics and Statistics Faculty and Staff Publications
In this paper, we present a Non-Bayesian conditioning rule for belief revision. This rule is truly Non-Bayesian in the sense that it doesn’t satisfy the common adopted principle that when a prior belief is Bayesian, after conditioning by X, Bel(X|X) must be equal to one. Our new conditioning rule for belief revision is based on the proportional conflict redistribution rule of combination developed in DSmT (Dezert-Smarandache Theory) which abandons Bayes’ conditioning principle. Such Non-Bayesian conditioning allows to take into account judiciously the level of conflict between the prior belief available and the conditional evidence. We also introduce the deconditioning problem …
Fusion Of Sources Of Evidence With Different Importances And Reliabilities, Florentin Smarandache, Jean Dezert, J.M. Tacnet
Fusion Of Sources Of Evidence With Different Importances And Reliabilities, Florentin Smarandache, Jean Dezert, J.M. Tacnet
Branch Mathematics and Statistics Faculty and Staff Publications
This paper presents a new approach for combining sources of evidences with different importances and reliabilities. Usually, the combination of sources of evidences with different reliabilities is done by the classical Shafer’s discounting approach. Therefore, to consider unequal importances of sources, if any, a similar reliability discounting process is generally used, making no difference between the notion of importance and reliability. In fact, in multicriteria decision context, these notions should be clearly distinguished. This paper shows how this can be done and we provide simple examples to show the differences between both solutions for managing importances and reliabilities of sources. …