Improved Synaptic Behavior Under Identical Pulses Using AlOx/HfO2 Bilayer RRAM Array for Neuromorphic Systems
By J. Woo, Kibong Moon, Jeonghwan Song, Sangheon Lee, Myounghun Kwak, Jaesung Park, Hyunsang Hwang. IEEE Electron Device Letters, 2016
366 citations recorded by the source corpus.
Subfields: Cognitive Neuroscience, Electrical and Electronic Engineering
View Paper: https://www.semanticscholar.org/paper/44bd42ecde6ffa31ca5aaa466ba471611f56217f
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In Cognitive Neuroscience
In Electrical and Electronic Engineering
Citations in the corpus
- NeuroSim: A Circuit-Level Macro Model for Benchmarking Neuro-Inspired Architectures in Online Learning (2018, background): “Such nonideal behaviors commonly exist in today’s synaptic devices [20]–[23], possibly due to the inherent drift and diffusion dynamics of the ions/vacancies in these materials.”
- Hardware implementation of memristor-based artificial neural networks (2024, neutral): “The weight update process is implemented by applying voltage or current pulses to the memristors (block 13 and 14), following the Write-Verify (or Close Loop Tunning) 194 – 196 , or the Write-without-Verify (or Open Loop Tunning) 103,107,197,198 .”
- Neuro-Inspired Computing With Emerging Nonvolatile Memorys (2018, methodology): “To make the SET process gradual, one way is the oxide stack engineering (i.e. bilayer oxides) to make weak or multiple weak filaments as demonstrated in TaOx/HfO2 [73] and AlOx/HfO2 [74] devices.”
- Fully hardware-implemented memristor convolutional neural network (2020, background): “Studies on memristor-based neuromorphic computing have covered a broad range of topics, from device optimization to system implementation 6,17–23 .”
- Improving Analog Switching in HfOx-Based Resistive Memory With a Thermal Enhanced Layer (2017, neutral): “such as Al/PCMO, TaOx/TiO2, HfO2/AlOx, etc [6]–[8].”
- Ferroelectric FET analog synapse for acceleration of deep neural network training (2017, background): “[2] J. Woo, et al., “Improved synaptic behavior under identical pulses using AlOx/HfO2 bilayer RRAM array for neuromorphic systems,” IEEE Electron Device Lett., 37, 8, 994–997, 2016.”
- A crossbar array of magnetoresistive memory devices for in-memory computing (2022, background): “Of the four NVMs that can be produced at volume—that is, resistive random-access memory 8–13 , phase-change random-access memory 14,15 , flash memory 16–19 and spin-transfer-torque magnetoresistive random-access memory (STT-MRAM, or MRAM for brevity) 20–22,25 , Here we fill this gap and implement…”