Approximating a non-homogeneous HMM with Dynamic Spatial Dirichlet Process

@article{Ren2008ApproximatingAN,
  title={Approximating a non-homogeneous HMM with Dynamic Spatial Dirichlet Process},
  author={Haijun Ren and Liang Wu and Predrag Neskovic and Leon N. Cooper},
  journal={2008 19th International Conference on Pattern Recognition},
  year={2008},
  pages={1-4}
}
In this work we present a model that uses a Dirichlet process (DP) with a dynamic spatial constraints to approximate a non-homogeneous hidden Markov model (NHMM). The coefficient of the spatial constraint, which is locally dependent on each site, modulates the time-variant transition probability matrix. In our model, we use the DP in combination with variational Bayesian inference to estimate the local coefficients and the time-dependent structure of the hidden states. In addition, the… CONTINUE READING