Neuromorphic computing with multi-memristive synapses-Reference-Cited by-同舟云学术

Neuromorphic computing with multi-memristive synapses

Published:2018-06-28 Issue:1 Volume:9 Page:
ISSN:2041-1723
Container-title:Nature Communications
language:en
Short-container-title:Nat Commun

Author:

Boybat Irem^ORCID,Le Gallo Manuel^ORCID,Nandakumar S. R.^ORCID,Moraitis Timoleon,Parnell Thomas,Tuma Tomas,Rajendran Bipin^ORCID,Leblebici Yusuf,Sebastian Abu^ORCID,Eleftheriou Evangelos

Publisher

Springer Science and Business Media LLC

Subject

General Physics and Astronomy,General Biochemistry, Genetics and Molecular Biology,General Chemistry

Link

http://www.nature.com/articles/s41467-018-04933-y.pdf

Reference64 articles.

1. LeCun, Y., Bengio, Y. & Hinton, G. Deep learning. Nature 521, 436–444 (2015).

2. Schemmel, J. et al. A wafer-scale neuromorphic hardware system for large-scale neural modeling. In Proc. IEEE International Symposium on Circuits and Systems (ISCAS), 1947–1950 (IEEE, Paris, France, 2010).

3. Painkras, E. et al. SpiNNaker: a 1-W 18-core system-on-chip for massively-parallel neural network simulation. IEEE J. Solid-State Circuits 48, 1943–1953 (2013).

4. Merolla, P. A. et al. A million spiking-neuron integrated circuit with a scalable communication network and interface. Science 345, 668–673 (2014).

5. Qiao, N. et al. A reconfigurable on-line learning spiking neuromorphic processor comprising 256 neurons and 128K synapses. Front. Neurosci. 9, 141 (2015).

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