Skip to main content
King Abdullah University of Science and Technology
Communication and Computing Systems Lab
CCSL
Communication and Computing Systems Lab
  • Home
  • People
    • All Profiles
    • Principal Investigator
    • Postdoctoral Fellows
    • Research Scientists
    • Research Staff
    • Students
    • Alumni
    • Former Members
  • Research
    • Wireless Communication
    • Body Area Network
    • AI Accelerator
    • All Projects
  • Publications
    • Publications
    • Google Scholar
    • DBLP
    • IEEE Xplore
    • KAUST Repository
    • ORCID
  • Events
  • Media Gallery
  • Contacts
  • Join us

synapses

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

Communication and Computing Systems Lab (CCSL)

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