Locally Connected Spiking Neural Networks for Unsupervised Feature Learning

@article{Saunders2019LocallyCS,
  title={Locally Connected Spiking Neural Networks for Unsupervised Feature Learning},
  author={D. J. Saunders and Devdhar Patel and Hananel Hazan and H. Siegelmann and R. Kozma},
  journal={Neural networks : the official journal of the International Neural Network Society},
  year={2019},
  volume={119},
  pages={
          332-340
        }
}
In recent years, spiking neural networks (SNNs) have demonstrated great success in completing various machine learning tasks. We introduce a method for learning image features with locally connected layers in SNNs using a spike-timing-dependent plasticity (STDP) rule. In our approach, sub-networks compete via inhibitory interactions to learn features from different locations of the input space. These locally-connected SNNs (LC-SNNs) manifest key topological features of the spatial interaction… Expand
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