Coexistence of short- and long-term memory in NbOx-based memristor for a nonlinear reservoir computing system

  • Jang, Heeseong
  • Heo, Jungang
  • Park, Jihee
  • Na, Hyesung
  • Kim, Sungjun
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초록

In this study, TiN/NbOX/Pt memristor devices with short-term memory (STM) and self-rectifying characteristics are used for reservoir computing. The STM characteristics of the device are detected using direct current sweep and pulse transients. The self-rectifying characteristics of the device can be explained by the work function differences between the TiN and Pt electrodes. Furthermore, neural network simulations were conducted for pattern recognition accuracy when the conductance was used as the synaptic weight. The emulation of synaptic memory and forgetfulness by short-term memory effects are demonstrated using paired-pulse facilitation and excitatory postsynaptic potential. The efficient training reservoir computing consisted of all 16 states (4-bit) in the memristor device as a physical reservoir and the artificial neural network simulation as a readout layer and yielded a pattern recognition accuracy of 92.34% for the modified National Institute of Standards and Technology dataset. Finally, it is found that STM and long-term memory in the device coexist by adjusting the intensity of pulse stimulation.

키워드

memristorresistive switchingneural networkreservoir computingSYNAPTIC PLASTICITYWORK FUNCTION
제목
Coexistence of short- and long-term memory in NbOx-based memristor for a nonlinear reservoir computing system
저자
Jang, HeeseongHeo, JungangPark, JiheeNa, HyesungKim, Sungjun
DOI
10.15302/frontphys.2025.014208
발행일
2025-02
유형
Article
저널명
Frontiers of Physics
20
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