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Synchronous Behavior for Memristive Synapse-Connected Chay Twin-Neuron Network and Hardware Implementation

Author

Listed:
  • Quan Xu
  • Xiao Tan
  • Dong Zhu
  • Mo Chen
  • Jie Zhou
  • Huagan Wu

Abstract

Synchronous behavior can be responsible for the function or dysfunction of a neural network. To employ a memristor with threshold memductance as a bidirectional synapse, a memristive synapse-connected Chay twin-neuron network is constructed. This paper numerically presents the synchronous behavior for four representative firing activities in the memristive twin-neuron network by utilizing time-domain waveforms, synchronized transition states (STSs), and mean synchronization errors (MSEs). Indeed, the synchronous behaviors are truly related to the coupling strength and initial condition of the memristor. Besides, utilizing the powerful XC7Z020 FPGA, a digitally circuit-implemented electro-neuron and the memristive synapse-connected Chay twin-neuron network are made. Thereafter, the four representative firing activities and their STSs are experimentally captured to further confirm the numerical simulations.

Suggested Citation

  • Quan Xu & Xiao Tan & Dong Zhu & Mo Chen & Jie Zhou & Huagan Wu, 2020. "Synchronous Behavior for Memristive Synapse-Connected Chay Twin-Neuron Network and Hardware Implementation," Mathematical Problems in Engineering, Hindawi, vol. 2020, pages 1-12, September.
    • Handle: RePEc:hin:jnlmpe:8218740
    DOI: 10.1155/2020/8218740
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