Least committed basic belief density induced by a multivariate Gaussian: Formulation with applications
CARON, Francois
Advanced Learning Evolutionary Algorithms [ALEA]
Institut de Mathématiques de Bordeaux [IMB]
See more >
Advanced Learning Evolutionary Algorithms [ALEA]
Institut de Mathématiques de Bordeaux [IMB]
CARON, Francois
Advanced Learning Evolutionary Algorithms [ALEA]
Institut de Mathématiques de Bordeaux [IMB]
< Reduce
Advanced Learning Evolutionary Algorithms [ALEA]
Institut de Mathématiques de Bordeaux [IMB]
Language
en
Article de revue
This item was published in
International Journal of Approximate Reasoning. 2008-06, vol. 48, n° 2, p. 419-436
Elsevier
English Abstract
We consider here the case where our knowledge is partial and based on a betting density function which is n-dimensional Gaussian. The explicit formulation of the least committed basic belief density (bbd) of the multivariate ...Read more >
We consider here the case where our knowledge is partial and based on a betting density function which is n-dimensional Gaussian. The explicit formulation of the least committed basic belief density (bbd) of the multivariate Gaussian pdf is provided in the transferable belief model (TBM) framework. Beliefs are then assigned to hyperspheres and the bbd follows a khi-2 distribution. Two applications are also presented. The first one deals with model based classification in the joint speed-accel- eration feature space. The second is devoted to joint target tracking and classification: the tracking part is performed using a Rao-Blackwellized particle filter, while the classification is carried out within the developed TBM scheme.Read less <
English Keywords
Belief function theory
Transferable belief model
Evidential theory
Multivariate Gaussian pdf
Target classification
Target tracking
Particle filtering
Origin
Hal imported