To the question of learnability of a spiking neuron with spike-timing-dependent plasticity in case of complex input signals

Alexander Sboev; Danila Vlasov; Alexey Serenko; Roman Rybka; Ivan Moloshnikov

Conference Proceedings

To the question of learnability of a spiking neuron with spike-timing-dependent plasticity in case of complex input signals

Sboev A
Vlasov D
Serenko A
et al.

Advances in Intelligent Systems and Computing (2016) 449 205-211

DOI: 10.1007/978-3-319-32554-5_26

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Abstract

Results of investigations of learnability of a spiking neuron in case of complex input signals which encode binary vectors are presented. The disadvantages of the supervised learning protocol with stimulating the neuron by current impulses in desired moments of time are analyzed.

Author supplied keywords

Computational neuroscience
Long-term synaptic plasticity
Neural networks
Spike-timing-dependent plasticity
Supervised learning

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Sboev, A., Vlasov, D., Serenko, A., Rybka, R., & Moloshnikov, I. (2016). To the question of learnability of a spiking neuron with spike-timing-dependent plasticity in case of complex input signals. In Advances in Intelligent Systems and Computing (Vol. 449, pp. 205–211). Springer Verlag. https://doi.org/10.1007/978-3-319-32554-5_26

To the question of learnability of a spiking neuron with spike-timing-dependent plasticity in case of complex input signals

Abstract

Author supplied keywords

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