Implementation of biologically plausible spiking neural network models on the memristor crossbar-based CMOS/nano circuits

ECCTD 2009 - European Conference on Circuit Theory and Design Conference Program

Volumn , Issue , 2009, Pages 563-566

  Afifi, A ^a   Ayatollahi, A ^a   Raissi, F ^b  

^a IRAN UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Iran)

^b K N TOOSI UNIVERSITY OF TECHNOLOGY   (Iran)

Author keywords

[No Author keywords available]

Indexed keywords

BIOLOGICAL ACTIONS; DYNAMIC LEARNING; LEARNING METHODS; LOCAL LEARNING; MEMRISTOR; NANO-DEVICES; NEUROMORPHIC NETWORKS; SPIKE TIMING; SPIKE TIMING DEPENDENT PLASTICITIES; SPIKING NEURAL NETWORKS;

CIRCUIT THEORY; NANOSTRUCTURED MATERIALS; NEURONS;

NEURAL NETWORKS;

EID: 71249131272     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ECCTD.2009.5275035     Document Type: Conference Paper

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