This paper describes a theory of data fusion in random-set formalism. Data fusion problems are defined as problems for estimating random sets of targets, i.e., an unknown number of objects whose states are to be estimated, based on information given in terms of random sets, i.e., a collection of sets of unknown numbers of observables with unknown origins. In this theory, information, i.e., a state of knowledge, is described, both a priori and a posteriori, in terms of random-set probability density functions, sometimes known as Janossy densities. Using this formalism, this paper considers an abstract distributed information processing system consisting of multiple information processing agents that, in addition to processing local informati...
This paper presents new methods for probabilistic belief revi-sion and information fusion. By making...
National audienceWhen multiple sources provide information about the same badly known quantity, aggr...
This paper is a subjective, short overview of algorithmic information theory. We critically discuss ...
Abstract- Until recently, data fusion problems have been solved heuristically using fuzzy logic, rul...
International audiencePossibility theory and the body of aggregation operations from fuzzy set theor...
bb International Centre for Mechanical SciencesInternational audiencePossibility theory and the body...
This work concerns an automatic information fusion scheme for state estimation where the inputs (or ...
The general purpose of data fusion consists in the combination of separately information, delivered ...
We introduce a robust approach to diagnostic information fusion within a network of probabilistic mo...
© 2015 IEEE. Finite-set statistics (FISST, a.k.a. random-set information fusion) was first systemati...
It is shown that the covariance intersection fusion rule, widely used in the context of distributed ...
We address the point of introducing fusion and representation techniques for distributed knowledge s...
This paper presents an information theoretic approach to the concept of intelligence in the com-puta...
We introduce a robust approach to diagnostic information fusion within a network of probabilistic mo...
Abstract. Depending on the representation setting, different combination rules have been proposed fo...
This paper presents new methods for probabilistic belief revi-sion and information fusion. By making...
National audienceWhen multiple sources provide information about the same badly known quantity, aggr...
This paper is a subjective, short overview of algorithmic information theory. We critically discuss ...
Abstract- Until recently, data fusion problems have been solved heuristically using fuzzy logic, rul...
International audiencePossibility theory and the body of aggregation operations from fuzzy set theor...
bb International Centre for Mechanical SciencesInternational audiencePossibility theory and the body...
This work concerns an automatic information fusion scheme for state estimation where the inputs (or ...
The general purpose of data fusion consists in the combination of separately information, delivered ...
We introduce a robust approach to diagnostic information fusion within a network of probabilistic mo...
© 2015 IEEE. Finite-set statistics (FISST, a.k.a. random-set information fusion) was first systemati...
It is shown that the covariance intersection fusion rule, widely used in the context of distributed ...
We address the point of introducing fusion and representation techniques for distributed knowledge s...
This paper presents an information theoretic approach to the concept of intelligence in the com-puta...
We introduce a robust approach to diagnostic information fusion within a network of probabilistic mo...
Abstract. Depending on the representation setting, different combination rules have been proposed fo...
This paper presents new methods for probabilistic belief revi-sion and information fusion. By making...
National audienceWhen multiple sources provide information about the same badly known quantity, aggr...
This paper is a subjective, short overview of algorithmic information theory. We critically discuss ...