Hebbian learning in spiking neural networks with nanocrystalline silicon TFTs and memristive synapses

IEEE Transactions on Nanotechnology

Volumn 10, Issue 5, 2011, Pages 1066-1073

  Cantley, Kurtis D ^a   Subramaniam, Anand ^a   Stiegler, Harvey J ^a   Chapman, Richard A ^a   Vogel, Eric M ^a  

^a The University of Texas at Dallas   (United States)

Author keywords

Hebbian learning; memristor; nanocrystalline silicon; neuromorphic; thin film transistors

Indexed keywords

3-D INTEGRATION; BIOLOGICAL NEURON; DEVICE MODELS; HEBBIAN LEARNING; MEASURED DATA; MEMRISTOR; NANOSCALE ARCHITECTURES; NEUROMORPHIC; NEURON CIRCUITS; POST-SYNAPTIC NEURONS; SPICE SIMULATIONS; SPIKING NEURAL NETWORKS; SPIKING NEURON; SUBMICRON; SYNAPTIC CONNECTIONS; SYNAPTIC PLASTICITY; SYNAPTIC WEIGHT;

MEMRISTORS; NANOCRYSTALLINE SILICON; NETWORKS (CIRCUITS); PASSIVE FILTERS; RESISTORS; SPICE; THIN FILM CIRCUITS; THIN FILM TRANSISTORS; THREE DIMENSIONAL;

NEURAL NETWORKS;

EID: 80052632703     PISSN: 1536125X     EISSN: None     Source Type: Journal    
DOI: 10.1109/TNANO.2011.2105887     Document Type: Article

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