26 search results - page 1 / 6 » Backpropagation for Population-Temporal Coded Spiking Neural... |
100
Voted
IJCNN
2006
IEEE
15 years 7 months ago
2006
IEEE
Abstract— Supervised learning rules for spiking neural networks are currently only able to use time-to-first-spike coding and are plagued by very irregular learning curves due t...
117
Voted
IJCNN
2008
IEEE
15 years 7 months ago
2008
IEEE
— Spiking neural networks have been shown capable of simulating sigmoidal artificial neural networks providing promising evidence that they too are universal function approximat...
125
Voted
ESANN
2000
15 years 2 months ago
2000
Abstract. For a network of spiking neurons with reasonable postsynaptic potentials, we derive a supervised learning rule akin to traditional error-back-propagation, SpikeProp and s...
86
Voted
CORR
2008
Springer
15 years 1 months ago
2008
Springer
Here is proposed a review of the different choices to structure spike trains, using deterministic metrics. Temporal constraints observed in biological or computational spike train...
109
Voted
FGCN
2008
IEEE
15 years 7 months ago
2008
IEEE
When recording extracellular neural activity, it is often necessary to distinguish action potentials arising from distinct cells near the electrode tip, a process commonly referre...