Community detection with spiking neural networks for neuromorphic hardware

@inproceedings{Hamilton2017CommunityDW,
  title={Community detection with spiking neural networks for neuromorphic hardware},
  author={Kathleen E. Hamilton and Neena Imam and Travis S. Humble},
  booktitle={NCS},
  year={2017}
}
We present results related to the performance of an algorithm for community detection which incorporates event-driven computation. We define a mapping which takes a graph 𝒢 to a system of symmetrically connected, spiking neurons and use spike train similarities to identify vertex communities. On a random graph with 128 vertices and known community structure we show how our approach can be used to identify individual communities from spiking neuron responses.