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Optimal state space partitioning

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1 Author(s)
Olivier, C. ; Lab. Syst. de Perception, ETCA, Arcueil, France

The partitioning problem of a parameter state space Ω into observation subsets is addressed. The initial knowledge about this parameter is a prior probability distribution over Ω. This distribution is recursively updated through parallel observation results, that are actually binary informations about the presence or the absence of the parameter inside subsets ωi of Ω. Each subset is scanned with some errors, corresponding to misdetections and false alarms. It is shown how the partitioning of Ω into the {ωi} may be optimized under different optimality criteria related to various measures of the “information” contained in the posterior probability density function. Simulations results are presented and computability issues are discussed

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Systems, Man and Cybernetics, IEEE Transactions on  (Volume:24 ,  Issue: 8 )