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RHLP_Matlab_v1

User-freindly and flexible algorithm for time series segmentation with a Regression model with a Hidden Logistic Process (RHLP).

If you are using this code, please cite the following papers:

@article{chamroukhi_et_al_NN2009,
	Address = {Oxford, UK, UK},
	Author = {Chamroukhi, F. and Sam\'{e}, A. and Govaert, G. and Aknin, P.},
	Date-Added = {2014-10-22 20:08:41 +0000},
	Date-Modified = {2014-10-22 20:08:41 +0000},
	Journal = {Neural Networks},
	Number = {5-6},
	Pages = {593--602},
	Publisher = {Elsevier Science Ltd.},
	Title = {Time series modeling by a regression approach based on a latent process},
	Volume = {22},
	Year = {2009},
	url  = {https://chamroukhi.com/papers/Chamroukhi_Neural_Networks_2009.pdf}
	}

@INPROCEEDINGS{Chamroukhi-IJCNN-2009,
  AUTHOR =       {Chamroukhi, F. and Sam\'e,  A. and Govaert, G. and Aknin, P.},
  TITLE =        {A regression model with a hidden logistic process for feature extraction from time series},
  BOOKTITLE =    {International Joint Conference on Neural Networks (IJCNN)},
  YEAR =         {2009},
  month = {June},
  pages = {489--496},
  Address = {Atlanta, GA},
 url = {https://chamroukhi.com/papers/chamroukhi_ijcnn2009.pdf}
}

@article{Chamroukhi-FDA-2018,
	Journal = {Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery},
	Author = {Faicel Chamroukhi and Hien D. Nguyen},
	Note = {DOI: 10.1002/widm.1298.},
	Volume = {},
	Title = {Model-Based Clustering and Classification of Functional Data},
	Year = {2019},
	Month = {to appear},
	url =  {https://chamroukhi.com/papers/MBCC-FDA.pdf}
	}

by Faicel Chamroukhi (since 2008)

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User-friendly and flexible algorithm for time-series segmentation by a Regression model with a Hidden Logistic Process (RHLP).

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