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Description
  • A slightly simplified version of the Spike Response Model SRM0 of a spiking neuron is tailored to gradient learning. In particular, the evolution of spike trains along the weight and delay parameter trajectories is made perfectly smooth. For this model a back-propagation-like learning rule is derived which propagates the error also along the time axis. This approach overcomes the difficulties with the discontinuous-in-time nature of spiking neurons, which encounter previous gradient learning algorithms (e.g. SpikeProp). The new algorithm can naturally cope with multiple spikes and preliminary experiments confirm the smoothness of spike creation/deletion process.
  • A slightly simplified version of the Spike Response Model SRM0 of a spiking neuron is tailored to gradient learning. In particular, the evolution of spike trains along the weight and delay parameter trajectories is made perfectly smooth. For this model a back-propagation-like learning rule is derived which propagates the error also along the time axis. This approach overcomes the difficulties with the discontinuous-in-time nature of spiking neurons, which encounter previous gradient learning algorithms (e.g. SpikeProp). The new algorithm can naturally cope with multiple spikes and preliminary experiments confirm the smoothness of spike creation/deletion process. (en)
Title
  • Gradient Learning in Networks of Smoothly Spiking Neurons
  • Gradient Learning in Networks of Smoothly Spiking Neurons (en)
skos:prefLabel
  • Gradient Learning in Networks of Smoothly Spiking Neurons
  • Gradient Learning in Networks of Smoothly Spiking Neurons (en)
skos:notation
  • RIV/67985807:_____/09:00318366!RIV10-MSM-67985807
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(1ET100300517), P(1M0545), Z(AV0Z10300504)
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 316608
http://linked.open...ai/riv/idVysledku
  • RIV/67985807:_____/09:00318366
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • spiking neuron; back-propagation; SpikeProp; gradient learning (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [0C217DE1929C]
http://linked.open...v/mistoKonaniAkce
  • Auckland
http://linked.open...i/riv/mistoVydani
  • Berlin
http://linked.open...i/riv/nazevZdroje
  • Advances in Neuro-Information Processing. Revised Selected Papers Part II
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Šíma, Jiří
http://linked.open...vavai/riv/typAkce
http://linked.open...ain/vavai/riv/wos
  • 000270578200022
http://linked.open.../riv/zahajeniAkce
http://linked.open...n/vavai/riv/zamer
number of pages
http://purl.org/ne...btex#hasPublisher
  • Springer-Verlag
https://schema.org/isbn
  • 978-3-642-03039-0
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