3 papers
cs.NE2020
Supervised Learning with First-to-Spike Decoding in Multilayer Spiking Neural Networks
Brian Gardner, André Grüning
Experimental studies support the notion of spike-based neuronal information processing in the brain, with neural circuits exhibiting a wide range of temporally-based coding strateg…
cs.NE2020
Supervised Learning in Temporally-Coded Spiking Neural Networks with Approximate Backpropagation
Andrew Stephan, Brian Gardner, Steven J. Koester +1
In this work we propose a new supervised learning method for temporally-encoded multilayer spiking networks to perform classification. The method employs a reinforcement signal tha…
eess.SP2018
An Introduction to Spiking Neural Networks: Probabilistic Models, Learning Rules, and Applications
Hyeryung Jang, Osvaldo Simeone, Brian Gardner +1
Spiking Neural Networks (SNNs) are distributed trainable systems whose computing elements, or neurons, are characterized by internal analog dynamics and by digital and sparse synap…