Inverse pignistic probability transforms

J.J. Sudano1
1Lockheed Martin, Moorestown, NJ, USA

Tóm tắt

In some information fusion processes, the incomplete information set can be naturally mapped into a belief theory information set and a Bayesian probability theory information set. For decision making, the mapping of the belief theory fusion results represented by the basic belief assignment to a probability set is accomplished via a pignistic probability transform. This article introduces the inverse pignistic probability transforms (IPPT) that map the posteriori probabilities into the belief function theories, basic belief assignments. Also introduced are two infinite classes and some finite classes of mapping the posteriori probability results to the basic belief assignment of the belief theory.

Từ khóa

#Bayesian methods #Real time systems #Sensor systems #Power measurement #Q measurement #Multidimensional systems #Information filtering #Information filters #Feature extraction #Natural languages

Tài liệu tham khảo

sudano, 2001, Pignistic probability transforms for mixes of low- and high-probability events, 2001 International Conference on Information Fusion 10.1016/0004-3702(94)90026-4