Skip to main content
Cyber Security and Resilience Community
Cyber Security and Resilience Community
People
Faculty
Research Scientists
Postdoctoral Fellows
All People
Research Groups
Cyber Security and Resilience Technology (CyberSaR)
Roberto Di Pietro Research Group (R-Pietro)
Security Research Bearing Experimental Results (SeRBER)
Research Strategy
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