Robust learning approach for neuro-Inspired nanoscale crossbar architecture

ACM Journal on Emerging Technologies in Computing Systems

Volumn 10, Issue 1, 2014, Pages

  Chabi, Djaafar ^a   Querlioz, Damien ^a   Zhao, Weisheng ^a   Klein, Jacques Olivier ^a  

^a CNRS   (France)

Author keywords

Defect and variation tolerance; Memristors; Nanoscale crossbar; Neural network; On Chip learning; Redundant design; Supervised learning

Indexed keywords

GLOBAL RELIABILITY; HARDWARE NEURAL NETWORKS; NANOSCALE CROSSBAR; ON-CHIP LEARNING; PARAMETER VARIABILITY; REDUNDANT DESIGN; SUPERVISED LEARNING METHODS; VARIATION TOLERANCES;

ANALYTICAL MODELS; DEFECTS; EXTRAPOLATION; MEMRISTORS; MODELS; MONTE CARLO METHODS; NANOTECHNOLOGY; NEURAL NETWORKS; REDUNDANCY; SUPERVISED LEARNING;

PASSIVE FILTERS;

EID: 84892581808     PISSN: 15504832     EISSN: 15504840     Source Type: Journal    
DOI: 10.1145/2539123     Document Type: Article

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