@InProceedings{ip-Urteaga2015b,
  author    = {I{\~n}igo Urteaga and M\'{o}nica F. Bugallo and Petar M Djuri\'{c}},
  title     = {{Filtering of nonlinear time-series coupled by fractional Gaussian processes}},
  booktitle = {2015 IEEE 6th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP)},
  year      = {2015},
  pages     = {489--492},
  abstract  = {In this paper we consider a set of time\-/series that are coupled by latent fractional Gaussian processes. Specifically, we address time\-/series that combine idiosyncratic short\-/term and shared long\-/term features. The long\-/memory is modeled by fractional Gaussian processes, whereas the short\-/memory properties are captured by linear models of past data. The observations are nonlinear functions of the hidden states and therefore we resort to a sequential Monte Carlo sampling technique for inference of the latent states. The proposed solution is evaluated via simulations of an illustrative practical scenario.},
  doi       = {http://dx.doi.org/10.1109/CAMSAP.2015.7383843},
  owner     = {iurteaga},
  timestamp = {2015-11-10},
}

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