activity
20172023
most citedA Survey of Neuromorphic Computing and Neural Networks in Hardware

363 citations · 433 across the 11 of their papers we have counts for

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Showing 2023Show all

5 papers · 1 filter

cs.ET2023

Reimagining Sense Amplifiers: Harnessing Phase Transition Materials for Current and Voltage Sensing

Md Mazharul Islam, Shamiul Alam, Mohammad Adnan Jahangir +5

Energy-efficient sense amplifier (SA) circuits are essential for reliable detection of stored memory states in emerging memory systems. In this work, we present four novel sense am…

cs.NE2023★ 5 cited

Functional Specification of the RAVENS Neuroprocessor

Adam Z. Foshie, James S. Plank, Garrett S. Rose +1

RAVENS is a neuroprocessor that has been developed by the TENNLab research group at the University of Tennessee. Its main focus has been as a vehicle for chip design with memristiv…

cs.ET2023★ 14 cited

Enhanced Read Resolution in Reconfigurable Memristive Synapses for Spiking Neural Networks

Hritom Das, Nishith N. Chakraborty, Catherine Schuman +1

Synapse is a key element of any neuromorphic computing system which is mostly constructed with memristor devices. A memristor is a two-terminal analog memory device. Memristive syn…

cs.NE2023★ 21 cited

An Efficient and Accurate Memristive Memory for Array-based Spiking Neural Networks

Hritom Das, Rocco D. Febbo, SNB Tushar +4

Memristors provide a tempting solution for weighted synapse connections in neuromorphic computing due to their size and non-volatile nature. However, memristors are unreliable in t…

cs.ET2023★ 24 cited

Optimizations for a Current-Controlled Memristor-based Neuromorphic Synapse Design

Hritom Das, Rocco D. Febbo, Charlie P. Rizzo +3

The synapse is a key element of neuromorphic computing in terms of efficiency and accuracy. In this paper, an optimized current-controlled memristive synapse circuit is proposed. O…