Skip to main content
Cyber Security and Resilience Technology
CyberSaR
Cyber Security and Resilience Technology
Main navigation
Home
Projects
People
All Profiles
Leadership Team
Affiliate Faculty
Research Scientists
Research Staff
Postdoctoral Fellows
Students
Team
Datasets
Startups
Synaptic Sampling Machine SSM
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