Extending SpikeProp

This paper introduces enhancements to the SpikeProp algorithm (S. M. Bohte, et al., 2002), an error-backpropagation learning rule suited for spiking neurons using exact spike time coding. These enhancements provide additional learning rules for the synaptic delays, time constants and for the neurons' thresholds. This results in less constrained network topologies (the XOR problem for example needs up to 10 times less weights and learning convergence is up to two times faster).