Results 91 to 100 of about 16,611 (244)

Ternary Content‐Addressable Memory Using One Capacitor and One Nanoelectromechanical Memory Switch for Data‐Intensive Applications

Advanced Intelligent Systems, EarlyView.
A charge‐domain ternary content‐addressable memory using one capacitor one nanoelectromechanical memory switch (1C‐1N TCAM) is proposed for energy‐efficient, high‐reliability computations. Integrated with the back‐end‐of‐line process, the 1C‐1N TCAM leverages the air gap capacitance to achieve a high capacitance ratio and ternary functionality.
Jin Wook Lee, Changha Kim, Geun Tae Park, Seung Hun Baek, Myeong Su Shin, Woo Young Choi   +5 more
wiley   +1 more source

Enhancing the Electrical Uniformity and Reliability of the HfO₂-Based RRAM Using High-Permittivity Ta₂O₅ Side Wall

IEEE Journal of the Electron Devices Society, 2018
In conventional HfO2-based resistive random access memory (RRAM), SiO2 is usually adopted as side wall spacer (low-k spacer) to define the device feature size. It is found that the forming voltage of the conventional HfO2 RRAM with SiO2 spacer rises when
Mei Yuan, Yi-Ting Tseng, Po-Hsun Chen, Chih-Cheng Shih, Hui-Chun Huang, Ting-Chang Chang, Xiaole Cui, Xinnan Lin, Shengdong Zhang, Hang Zhou   +9 more
doaj   +1 more source

SiOx-based resistive switching memory integrated in nanopillar structure fabricated by nanosphere lithography [PDF]

, 2014
textA highly compact, one diode-one resistor (1D-1R) SiOx-based resistive switching memory device with nano-pillar architecture has been achieved for the first time using nano-sphere lithography. The average nano-pillar height and diameter are 1.3 μm and
Ji, Li, active 21st century
core  

Large‐Scale and Highly Reliable Hopfield Neural Networks Using Vertical NAND Flash Memory for the In‐Memory Associative Computing

Advanced Intelligent Systems, EarlyView.
Large‐scale Hopfield neural networks (HNNs) for associative computing are implemented using vertical NAND (VNAND) flash memory. The proposed VNAND HNN with the asynchronous update scenario achieve robust image restoration performance despite fabrication variations, while significantly reducing chip area (≈117× smaller than resistive random‐access ...
Jin Ho Chang, Jae Seung Woo, Suk‐Kang Sung, Ki‐Whan Song, Woo Young Choi   +4 more
wiley   +1 more source

Exploring Resistive Switching in Novel Amorphous Phosphate Glasses for Next‐Generation Memory Applications

Advanced Intelligent Systems, EarlyView.
This study explores amorphous phosphate semiconductor glass for resistive random access memory (RRAM) applications. The nanodevices exhibit distinct resistive switching via trap‐assisted tunneling, space‐charge‐limited current, and Ohmic transport.
Hong‐Lin Lu, Yu‐Chi Chen, Jui‐Yuan Chen   +2 more
wiley   +1 more source

Review of Memristors for In‐Memory Computing and Spiking Neural Networks

Advanced Intelligent Systems, EarlyView.
Memristors uniquely enable energy‐efficient, brain‐inspired computing by acting as both memory and synaptic elements. This review highlights their physical mechanisms, integration in crossbar arrays, and role in spiking neural networks. Key challenges, including variability, relaxation, and stochastic switching, are discussed, alongside emerging ...
Mostafa Shooshtari, Teresa Serrano‐Gotarredona, Bernabé Linares‐Barranco   +2 more
wiley   +1 more source

Design and Application of Oxide-Based Resistive Switching Devices for Novel Computing Architectures

IEEE Journal of the Electron Devices Society, 2016
Resistive switching behaviors of oxide-based resistive random access memory (RRAM) and the applications for the data storage and computing systems have been widely studied.
Jinfeng Kang, Peng Huang, Bin Gao, Haitong Li, Zhe Chen, Yudi Zhao, Chen Liu, Lifeng Liu, Xiaoyan Liu   +8 more
doaj   +1 more source

RRAM based neuromorphic algorithms

, 2019
This submission is a report on RRAM based neuromorphic algorithms. This report basically gives an overview of the algorithms implemented on neuromorphic hardware with crossbar array of RRAM synapses. This report mainly talks about the work on deep neural network to spiking neural network conversion and its significance.
openaire   +2 more sources

Ferroelectric Tunnel Junction Memristor Crossbar Array with Annealing Optimization for In‐Memory Computing

Advanced Intelligent Systems, EarlyView.
A 48 × 48 ferroelectric tunnel junction (FTJ) crossbar array is fabricated and optimized through postmetallization annealing, enabling stable polarization switching and reliable multilevel conductance programming. Half‐bias operation, accurate vector–matrix multiplication with less than 1% error, and CIFAR‐10 image classification with near‐software ...
Sangwook Youn, Hwiho Hwang, Hyungjin Kim
wiley   +1 more source

A Fully Integrated Analog Processing‐in‐Memory System Based on Charge‐Trap Flash Synapse Arrays and Successive Integration‐and‐Rescaling Neurons

Advanced Intelligent Systems, EarlyView.
A fully integrated analog processing‐in‐memory system is demonstrated, combining charge‐trap flash synapse arrays with a successive integration‐and‐rescaling neuron circuit. The architecture performs bit‐sliced analog accumulation with high linearity and low power, achieving efficient and scalable analog in‐memory computing and bridging device‐level ...
Sojoong Kim, Yeonwoo Kim, Woo Young Choi, Minsuk Koo, Yoon Kim   +4 more
wiley   +1 more source