Highly Linear and Symmetric Weight Modification in HfO2‐Based Memristive Devices for High‐Precision Weight Entries
Sign Up to like & getrecommendations! Published in 2020 at "Advanced Electronic Materials"
DOI: 10.1002/aelm.202000434
Abstract: In this study, highly reliable and accurate weight‐modification behaviors are realized using a W/Al2O3 (3 nm)/HfO2 (7 nm)/TiN memristive device. The accuracy of the simulated inference of the MNIST dataset when considering the weight‐modification behavior… read more here.
Keywords: hfo2; linear symmetric; weight modification; modification ... See more keywords
Linear and Symmetric Li-Based Composite Memristors for Efficient Supervised Learning.
Sign Up to like & getrecommendations! Published in 2022 at "ACS applied materials & interfaces"
DOI: 10.1021/acsami.1c24562
Abstract: Emerging energy-efficient neuromorphic circuits are based on hardware implementation of artificial neural networks (ANNs) that employ the biomimetic functions of memristors. Specifically, crossbar array memristive architectures are able to perform ANN vector-matrix multiplication more efficiently… read more here.
Keywords: symmetric based; memristors efficient; based composite; linear symmetric ... See more keywords
Resistive Memory-Based Analog Synapse: The Pursuit for Linear and Symmetric Weight Update
Sign Up to like & getrecommendations! Published in 2018 at "IEEE Nanotechnology Magazine"
DOI: 10.1109/mnano.2018.2844902
Abstract: This article reviews the recent developments in a type of random access memory (RAM) called resistive RAM (RRAM) for the analog synapse, which is an important building block for neuromorphic computing systems. To achieve high… read more here.
Keywords: symmetric weight; weight update; analog; analog synapse ... See more keywords