Towards using Reservoir Computing Networks for noise-robust image recognition

@article{Jalalvand2016TowardsUR,
  title={Towards using Reservoir Computing Networks for noise-robust image recognition},
  author={Azarakhsh Jalalvand and Wesley De Neve and Rik Van de Walle and Jean-Pierre Martens},
  journal={2016 International Joint Conference on Neural Networks (IJCNN)},
  year={2016},
  pages={1666-1672}
}
Reservoir Computing Network (RCN) is a special type of the single layer recurrent neural networks, in which the input and the recurrent connections are randomly generated and only the output weights are trained. Besides the ability to process temporal information, the key points of RCN are easy training and robustness against noise. Recently, we introduced a simple strategy to tune the parameters of RCN resulted in an effective and noise-robust RCN-based model for speech recognition. The aim of… CONTINUE READING

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