SpikeProp: backpropagation for networks of spiking neurons

@inproceedings{Bohte2000SpikePropBF,
  title={SpikeProp: backpropagation for networks of spiking neurons},
  author={Sander M. Bohte and Joost N. Kok and Han La Poutr{\'e}},
  booktitle={ESANN},
  year={2000}
}
For a network of spiking neurons with reasonable postsynaptic potentials, we derive a supervised learning rule akin to traditional error-back-propagation, SpikeProp and show how to overcome the discontinuities introduced by thresholding. Using this learning algorithm, we demonstrate how networks of spiking neurons with biologically plausible time-constants can perform complex non-linear classification in fast temporal coding just as well as rate-coded networks. When comparing the (implicit… CONTINUE READING

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2 Computing with Spiking Neurons

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Spike - prop : error - backprogation in multi - layer networks of spiking neurons

J. N. Kok, H. La Poutré
-1

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