Modeling and Unsupervised Classification of Multivariate Hidden Markov Chains With Copulas

@article{Brunel2010ModelingAU,
  title={Modeling and Unsupervised Classification of Multivariate Hidden Markov Chains With Copulas},
  author={Nicolas J.-B. Brunel and J{\'e}r{\^o}me Lapuyade-Lahorgue and Wojciech Pieczynski},
  journal={IEEE Transactions on Automatic Control},
  year={2010},
  volume={55},
  pages={338-349}
}
Parametric modeling and estimation of non-Gaussian multidimensional probability density function is a difficult problem whose solution is required by many applications in signal and image processing. A lot of efforts have been devoted to escape the usual Gaussian assumption by developing perturbed Gaussian models such as spherically invariant random vectors (SIRVs). In this work, we introduce an alternative solution based on copulas that enables theoretically to represent any multivariate… 
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