Skip to main content
King Abdullah University of Science and Technology
Applied Mathematics and Computational Science
AMCS
Applied Mathematics and Computational Science
  • Study
    • Prospective Students
    • Current Students
  • Research
    • Research Areas
    • Research Groups
  • People
    • All People
    • Faculty
    • Affiliate Faculty
    • Instructional Faculty
    • Research Scientists
    • Research Staff
    • Postdoctoral Fellows
    • Administrative Staff
    • Alumni
    • Students
  • News
  • Events
  • SIAM Student Chapter
  • CEMSE Division
  • About
  • Apply

biological

Memristor-based Synaptic Sampling Machines

1 min read · Thu, Apr 26 2018

News

biological neural network Biosensors synapses Synaptic Sampling Machine SSM

Dolzhikova, I, et al., "Memristor-based Synaptic Sampling Machines. In 2018 IEEE 18th International Conference on Nanotechnology (IEEE-NANO), 2018, 425. Synaptic Sampling Machine (SSM) is a type of neural network model that considers biological unreliability of the synapses. We propose the circuit design of the SSM neural network which is realized through the memristive-CMOS crossbar structure with the synaptic sampling cell (SSC) being used as a basic stochastic unit. The increase in the edge computing devices in the Internet of things era, drives the need for hardware acceleration for data

Applied Mathematics and Computational Science (AMCS)

Footer

  • A-Z Directory
    • All Content
    • Browse Related Sites
  • Site Management
    • Log in

© 2025 King Abdullah University of Science and Technology. All rights reserved. Privacy Notice