Bioinspired networks with nanoscale memristive devices that combine the unsupervised and supervised learning approaches

Proceedings of the 2012 IEEE/ACM International Symposium on Nanoscale Architectures, NANOARCH 2012

Volumn , Issue , 2012, Pages 203-210

  Querlioz, D ^a   Zhao, W S ^a   Dollfus, P ^a   Klein, J O ^a   Bichler, O ^b   Gamrat, C ^b  

^a UNIVERSITÉ PARIS SACLAY   (France)

^b DIF   (France)

Author keywords

device variations; learning architecture; memristive devices; neuroinspired systems; supervised learning; synapses; unsupervised learning

Indexed keywords

ARCHITECTURE; CHARACTER RECOGNITION; EFFICIENCY; MACHINE LEARNING; NANOSTRUCTURED MATERIALS; NETWORK ARCHITECTURE; SUPERVISED LEARNING; UNSUPERVISED LEARNING;

BIO-INSPIRED NETWORKS; DEVICE VARIATIONS; LEARNING ARCHITECTURES; MEMRISTIVE DEVICES; SPIKE TIMING DEPENDENT PLASTICITIES; SUPERVISED LEARNING APPROACHES; SYNAPSES; UNSUPERVISED APPROACHES;

MEMRISTORS;

EID: 84874769788     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2765491.2765528     Document Type: Conference Paper

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