A Silicon Synapse Based on a Charge Transfer Device for Spiking Neural Network Application

  • Yajie Chen
  • Steve Hall
  • Liam McDaid
  • Octavian Buiu
  • Peter Kelly
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3973)


We propose a silicon synapse for spiking neural network application. In this endeavor, two major issues are addressed: the structure of the synapse and the associated behavior. This synaptic structure is basically a charge transfer device comprising of two Metal-Oxide-Semiconductor (MOS) capacitors the first of which stores the weight and the second controls its reading. In this work, simulation results prove that the proposed synapse captures the intrinsic dynamics of the biological synapse and exhibits a spike characteristic. The device operates at very low power and offers the potential for scaling to massively parallel third generation hardware neural networks.


Inversion Layer Charge Transfer Process Postsynaptic Neuron Output Terminal Synaptic Structure 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Yajie Chen
    • 1
  • Steve Hall
    • 1
  • Liam McDaid
    • 2
  • Octavian Buiu
    • 1
  • Peter Kelly
    • 2
  1. 1.Department of Electrical Engineering and ElectronicsUniversity of LiverpoolLiverpoolUK
  2. 2.School of Computing and Intelligent SystemsUniversity of UlsterLondonderry, Northern IrelandUK

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