HfO2-Based OxRAM Devices as Synapses for Convolutional Neural Networks

IEEE Transactions on Electron Devices

Volumn 62, Issue 8, 2015, Pages 2494-2501

  Garbin, Daniele ^a,b   Vianello, Elisa ^a,b   Bichler, Olivier ^c   Rafhay, Quentin ^d   Gamrat, Christian ^c   Ghibaudo, Gerard ^d   DeSalvo, Barbara ^a,b   Perniola, Luca ^a,b  

^a UNIV GRENOBLE ALPES   (France)

^b CEA LETI   (France)

^c DIF   (France)

^d Inst de Microélectronique Électromagnétisme   (France)

Author keywords

Convolutional neural network (CNN); resistive RAM (RRAM) synapse; spike timing dependent plasticity (STDP); stochastic neuromorphic system; visual pattern extraction.

Indexed keywords

COMPLEX NETWORKS; CONVOLUTION; NEURAL NETWORKS; NEURONS; OXYGEN VACANCIES; RANDOM ACCESS STORAGE; STOCHASTIC MODELS; STOCHASTIC SYSTEMS;

CONVOLUTIONAL NEURAL NETWORK; NEUROMORPHIC SYSTEMS; RESISTIVE RAMS (RRAM); SPIKE TIMING DEPENDENT PLASTICITIES; VISUAL PATTERN;

PATTERN RECOGNITION;

EID: 85027929720     PISSN: 00189383     EISSN: None     Source Type: Journal    
DOI: 10.1109/TED.2015.2440102     Document Type: Article

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