An online supervised learning algorithm based on triple spikes for spiking neural networks

6 Jan 2019Guojun ChenXianghong LinGuoen Wang

Using precise times of every spike, spiking supervised learning has more effects on complex spatial-temporal pattern than supervised learning only through neuronal firing rates. The purpose of spiking supervised learning after spatial-temporal encoding is to emit desired spike trains with precise times... (read more)

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