Forming-Less Compliance-Free Multistate Memristors as Synaptic Connections for Brain-Inspired Computing
Author:
Affiliation:
1. School of Materials Science and Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798, Singapore
2. Energy Research Institute@NTU (ERI@N), Nanyang Technological University, Singapore 637553, Singapore
Funder
Ministry of Education - Singapore
Publisher
American Chemical Society (ACS)
Subject
Materials Chemistry,Electrochemistry,Electronic, Optical and Magnetic Materials
Link
https://pubs.acs.org/doi/pdf/10.1021/acsaelm.0c00002
Reference35 articles.
1. Beyond von‐Neumann Computing with Nanoscale Phase‐Change Memory Devices
2. Flexible Ionic-Electronic Hybrid Oxide Synaptic TFTs with Programmable Dynamic Plasticity for Brain-Inspired Neuromorphic Computing
3. Neuromorphic computing using non-volatile memory
4. Memristor-Based Multilayer Neural Networks With Online Gradient Descent Training
5. Nanoscale Memristor Device as Synapse in Neuromorphic Systems
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2. Memristors with tunable characteristics based on the tellurene/Nb-doped MoS2 heterojunction toward bio-realistic synaptic emulation;Applied Physics Letters;2023-10-23
3. Reproducible Non-Volatile Multi-State Storage and Emulation of Synaptic Plasticity Based on a Copper-Nanoparticle-Embedded HfOx/ZnO Bilayer with Ultralow-Switching Current and Ideal Data Retention;Nanomaterials;2022-10-26
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