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Erick De La Rosa
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Cited by
Year
Randomized algorithms for nonlinear system identification with deep learning modification
E De la Rosa, W Yu
Information Sciences 364, 197-212, 2016
822016
Data-driven fuzzy modeling using restricted Boltzmann machines and probability theory
E De la Rosa, W Yu
IEEE Transactions on Systems, Man, and Cybernetics: Systems 50 (7), 2316-2326, 2018
362018
Nonlinear system modeling with deep neural networks and autoencoders algorithm
E De la Rosa, W Yu, X Li
2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC …, 2016
162016
Nonlinear system identification using deep learning and randomized algorithms
E De la Rosa, W Yu, X Li
2015 IEEE International Conference on Information and Automation, 274-279, 2015
142015
Restricted Boltzmann machine for nonlinear system modeling
E De la Rosa, W Yu
2015 IEEE 14th International conference on machine learning and applications …, 2015
132015
Deep Boltzmann machine for nonlinear system modelling
W Yu, E De la Rosa
International Journal of Machine Learning and Cybernetics 10, 1705-1716, 2019
72019
Neural Modeling With Guaranteed Input–Output Probability Distributions
W Yu, E De la Rosa
IEEE Transactions on Systems, Man, and Cybernetics: Systems 51 (11), 6660-6668, 2020
52020
Probability based fuzzy modeling
B de la Rosa, W Yu, X Li
2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC …, 2017
42017
Fuzzy modeling from black-box data with deep learning techniques
E De la Rosa, W Yu, H Sossa
Advances in Neural Networks-ISNN 2017: 14th International Symposium, ISNN …, 2017
12017
Conditional probability calculation using restricted Boltzmann machine with application to system identification
E De la Rosa, W Yu
arXiv preprint arXiv:1806.02499, 2018
2018
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