File Classification Based on Spiking Neural Networks

@article{Stanojevi2020FileCB,
  title={File Classification Based on Spiking Neural Networks},
  author={Ana Stanojevi{\'c} and Giovanni Cherubini and Timoleon Moraitis and Abu Sebastian},
  journal={2020 IEEE International Symposium on Circuits and Systems (ISCAS)},
  year={2020},
  pages={1-5}
}
In this paper, we propose a system for file classification in large data sets based on spiking neural networks (SNNs). File information contained in key-value metadata pairs is mapped by a novel correlative temporal encoding scheme to spike patterns that are input to an SNN. The correlation between input spike patterns is determined by a file similarity measure. Unsupervised training of such networks using spike-timing-dependent plasticity (STDP) is addressed first. Then, supervised SNN… 

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