Unsupervised Learning in Reservoir Computing for EEG-Based Emotion Recognition

@article{Fourati2022UnsupervisedLI,
  title={Unsupervised Learning in Reservoir Computing for EEG-Based Emotion Recognition},
  author={Rahma Fourati and Boudour Ammar and Javier J. S{\'a}nchez Medina and Adel M. Alimi},
  journal={IEEE Transactions on Affective Computing},
  year={2022},
  volume={13},
  pages={972-984}
}
In real-world applications such as emotion recognition from recorded brain activity, data are captured from electrodes over time. These signals constitute a multidimensional time series. In this article, Echo State Network (ESN), a recurrent neural network with great success in time series prediction and classification, is optimized with different neural plasticity rules for classification of emotions based on electroencephalogram (EEG) time series. The developed network could automatically… 

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