Extraction of temporally correlated features from dynamic vision sensors with spike-timing-dependent plasticity

Neural Networks

Volumn 32, Issue , 2012, Pages 339-348

  Bichler, Olivier ^a   Querlioz, Damien ^b   Thorpe, Simon J ^c   Bourgoin, Jean Philippe ^d   Gamrat, Christian ^a  

^a DIF   (France)

^b UNIVERSITÉ PARIS SACLAY   (France)

^c Brain and Cognition Research Center in Toulouse   (France)

^d Laboratoire d Electronique Moléculaire   (France)

Author keywords

Dynamic vision sensor; Features extraction; Silicon retina; Spike timing dependent plasticity; Spiking neural network; Unsupervised learning

Indexed keywords

DYNAMIC VISION; FEATURES EXTRACTION; SILICON RETINA; SPIKE-TIMING-DEPENDENT PLASTICITY; SPIKING NEURAL NETWORKS;

NEURAL NETWORKS; UNSUPERVISED LEARNING;

PIXELS;

ARTICLE; ARTIFICIAL NEURAL NETWORK; EVOLUTIONARY ALGORITHM; GENETIC ALGORITHM; IMAGE PROCESSING; LEARNING ALGORITHM; NERVE CELL PLASTICITY; POSTSYNAPTIC INHIBITION; PRIORITY JOURNAL; SIGNAL NOISE RATIO; SIGNAL PROCESSING; SPIKE TIMING DEPENDENT PLASTICITY; SPIKE WAVE; SYNAPTIC POTENTIAL; SYSTEM ANALYSIS;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; COMPUTER SIMULATION; LONG-TERM POTENTIATION; MODELS, GENETIC; MOTOR VEHICLES; NEURAL NETWORKS (COMPUTER); NEURONAL PLASTICITY; NEURONS; REPRODUCIBILITY OF RESULTS; RETINA; SIGNAL-TO-NOISE RATIO; SILICON; SYNAPSES; SYNAPTIC TRANSMISSION;

EID: 84861765357     PISSN: 08936080     EISSN: 18792782     Source Type: Journal    
DOI: 10.1016/j.neunet.2012.02.022     Document Type: Article

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