Training spiking neural networks to associate spatio-temporal input-output spike patterns

Neurocomputing

Volumn 107, Issue , 2013, Pages 3-10

  Mohemmed, Ammar ^a   Schliebs, Stefan ^a   Matsuda, Satoshi ^c   Kasabov, Nikola ^a,b  

^a AUCKLAND UNIVERSITY OF TECHNOLOGY   (New Zealand)

^b UNIVERSITY OF ZURICH   (Switzerland)

^c NIHON UNIVERSITY   (Japan)

Author keywords

Spatio temporal control; Spiking neural networks; Supervised learning; Temporal coding

Indexed keywords

ACCURACY OF CLASSIFICATIONS; ANALOGUE SIGNALS; MATHEMATICAL FORMULATION; NEUROREHABILITATION; SPATIO-TEMPORAL; SPATIOTEMPORAL PATTERNS; SPIKING NEURAL NETWORKS; TEMPORAL CODING;

LEARNING ALGORITHMS; NEURONS; SUPERVISED LEARNING;

NEURAL NETWORKS;

ACCURACY; ALGORITHM; ANALYTIC METHOD; ARTICLE; CALCULATION; INTERMETHOD COMPARISON; LEARNING; MATHEMATICAL MODEL; MOTOR CONTROL; NERVE CELL NETWORK; PRIORITY JOURNAL; SIMULATION; SPIKE PATTERN ASSOCIATION NEURON; SPIKING NEURAL NETWORK; SYNAPSE;

EID: 84875229251     PISSN: 09252312     EISSN: 18728286     Source Type: Journal    
DOI: 10.1016/j.neucom.2012.08.034     Document Type: Article

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