Contribution of belief functions to hidden markov models with an application to fault diagnosis

Evidence-theoretic propagations of temporal belief functions are proposed to deal with possibly dependent observations and for partially supervised learning of HMM. Solutions are formulated in Transferable Belief Model framework and experiments concern a diagnosis problem.