%0 Journal Article
%T Second-Order Belief Hidden Markov Models
%A Jungyeul Park
%A Mouna Chebbah
%A Siwar Jendoubi
%A Arnaud Martin
%J Computer Science
%D 2015
%I arXiv
%R 10.1007/978-3-319-11191-9_31
%X Hidden Markov Models (HMMs) are learning methods for pattern recognition. The probabilistic HMMs have been one of the most used techniques based on the Bayesian model. First-order probabilistic HMMs were adapted to the theory of belief functions such that Bayesian probabilities were replaced with mass functions. In this paper, we present a second-order Hidden Markov Model using belief functions. Previous works in belief HMMs have been focused on the first-order HMMs. We extend them to the second-order model.
%U http://arxiv.org/abs/1501.05613v1