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RHLP_Matlab_v1

version 1.0.0 (31.7 KB) by Faicel Chamroukhi
RHLP_Matlab_v1

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Updated 06 Dec 2018

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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.users.lmno.cnrs.fr/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.users.lmno.cnrs.fr/papers/chamroukhi_ijcnn2009.pdf} }

@article{Chamroukhi-FDA-2018, Journal = {}, Author = {Faicel Chamroukhi and Hien D. Nguyen}, Volume = {}, Title = {Model-Based Clustering and Classification of Functional Data}, Year = {2018}, eprint ={arXiv:1803.00276v2}, url = {https://chamroukhi.users.lmno.cnrs.fr/papers/MBCC-FDA.pdf} }

by Faicel Chamroukhi (since 2008)

Cite As

Faicel Chamroukhi (2019). RHLP_Matlab_v1 (https://www.github.com/fchamroukhi/RHLP_Matlab_v1), GitHub. Retrieved .

@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.users.lmno.cnrs.fr/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.users.lmno.cnrs.fr/papers/chamroukhi_ijcnn2009.pdf} } @article{Chamroukhi-FDA-2018, Journal = {}, Author = {Faicel Chamroukhi and Hien D. Nguyen}, Volume = {}, Title = {Model-Based Clustering and Classification of Functional Data}, Year = {2018}, eprint ={arXiv:1803.00276v2}, url = {https://chamroukhi.users.lmno.cnrs.fr/papers/MBCC-FDA.pdf} }

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MATLAB Release Compatibility
Created with R2018b
Compatible with any release
Platform Compatibility
Windows macOS Linux