Improving SpikeProp : Enhancements to An Error-Backpropagation Rule for Spiking Neural Networks

@inproceedings{Schrauwen2004ImprovingS,
  title={Improving SpikeProp : Enhancements to An Error-Backpropagation Rule for Spiking Neural Networks},
  author={Benjamin Schrauwen and Jan Van Campenhout},
  year={2004}
}
In this paper, enhancements to the SpikeProp learning algorithm [1] are presented. SpikeProp is an errorbackpropagation learning rule suited for supervised learning of spiking neurons that use exact spike time coding. These enhancements provide additional learning rules for the synaptic delays and time constants and for the neurons’ thresholds. This results in smaller network topologies. The simple XOR problem for example needs up to 10 times less weights and learning convergence is up to two… CONTINUE READING