Results 61 to 70 of about 11,242 (219)

First Order Rate Law Analysis for Reset State in Vanadium Oxide Thin Film Resistive Random Access Memory Devices

Nanomaterials, 2023
In the reset state, the decay reaction mechanism and bipolar switching properties of vanadium oxide thin film RRAM devices for LRS/HRS are investigated and discussed here.
Kai-Huang Chen, Chien-Min Cheng, Na-Fu Wang, Hsiao-Wen Hung, Cheng-Ying Li, Sean Wu   +5 more
semanticscholar   +1 more source

Accurate Inference With Inaccurate RRAM Devices: A Joint Algorithm-Design Solution

IEEE Journal on Exploratory Solid-State Computational Devices and Circuits, 2020
Resistive random access memory (RRAM) is a promising technology for energy-efficient neuromorphic accelerators. However, when a pretrained deep neural network (DNN) model is programmed to an RRAM array for inference, the model suffers from accuracy ...
Gouranga Charan, Abinash Mohanty, Xiaocong Du, Gokul Krishnan, Rajiv V. Joshi, Yu Cao   +5 more
doaj   +1 more source

Harnessing Time‐Dependent Magnetic Texture Dynamics via Spin‐Orbit Torque for Physics‐Enhanced Neuromorphic Computing

Advanced Science, EarlyView.
A neuromorphic computing platform using spin‐orbit torque‐controlled magnetic textures is reported. The device implements bio‐inspired synaptic functions and achieves high performance in both pattern recognition (>93%) and combinatorial optimization (>95%), enabling unified processing of cognitive and optimization tasks.
Yifan Zhang, Yu Li, Huai Lin, Xinying Wang, Long Liu, Guoliang Xing, Di Wang, Zhihao Zhao, Zhipeng Guo, Junbo Yang, Jiebin Niu, Yan Sun, Tom Wu, Guozhong Xing   +13 more
wiley   +1 more source

A novel read circuit for RRAM based on RC delay effect

Electronics Letters, 2023
In this paper, a novel Resistive Random‐Access Memory (RRAM) read circuit has been designed and verified by simulation based on the RRAM model and parasitic capacitance of the circuit.
Jiabao Ye, Xuecheng Cui, Haoxiong Bi, Jifang Cao, Wannian Wang, Xiaoxin Xu, Dong Liu, Bing Chen   +7 more
doaj   +1 more source

A Fast Weight Transfer Method for Real-Time Online Learning in RRAM-Based Neuromorphic System

IEEE Access, 2022
In this work, a synaptic weight transfer method for a neuromorphic system based on resistive-switching random-access memory (RRAM) is proposed and validated.
Min-Hwi Kim, Sin-Hyung Lee, Sungjun Kim, Byung-Gook Park   +3 more
doaj   +1 more source

The over-reset phenomenon in Ta2O5 RRAM device investigated by the RTN-based defect probing technique [PDF]

, 2018
IEEE Despite the tremendous efforts in the past decade devoted to the development of filamentary resistive-switching devices (RRAM), there is still a lack of in-depth understanding of its over-reset phenomenon. At higher reset stop voltages that exceed a
Chai, Z, Chalker, P, Freitas, P, Goux, L, Govoreanu, B, Hall, S, Hatem, F, Kar, GS, Marsland, J, Robertson, J, Zhang, JF, Zhang, WD   +11 more
core   +2 more sources

In Situ Quantization with Memory‐Transistor Transfer Unit Based on Electrochemical Random‐Access Memory for Edge Applications

Advanced Science, EarlyView.
By combining ionic nonvolatile memories and transistors, this work proposes a compact synaptic unit to enable low‐precision neural network training. The design supports in situ weight quantization without extra programming and achieves accuracy comparable to ideal methods. This work obtains energy consumption advantage of 25.51× (ECRAM) and 4.84× (RRAM)
Zhen Yang, Yuxiang Yang, Baiqian Wang, Yaoyu Tao, Zelun Pan, Lei Cai, Teng Zhang, Longhao Yan, Xianbin Li, Yuchao Yang   +9 more
wiley   +1 more source

RRAM Based Random Bit Generation for Hardware Security Applications [PDF]

, 2016
© 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new
Arumi Delgado, Daniel, Manich Bou, Salvador, Pehl, Michael, Rodríguez Montañés, Rosa   +3 more
core   +1 more source

Oxide Semiconductor Thin‐Film Transistors for Low‐Power Electronics

Advanced Science, EarlyView.
This review explores the progress of oxide semiconductor thin‐film transistors in low‐power electronics. It illustrates the inherent material advantages of oxide semiconductor, which enable it to meet the low‐power requirements. It also discusses current strategies for reducing power consumption, including interface and structure engineering.
Shuhui Ren, Qi Huang, Dingwei Li, Saisai Wang, Yitong Chen, Huihui Ren, Yan Wang, Yingjie Tang, Bowen Zhu   +8 more
wiley   +1 more source

Multi-Level Resistive Al/Ga₂O₃/ITO Switching Devices with Interlayers of Graphene Oxide for Neuromorphic Computing

Nanomaterials, 2023
Recently, resistive random access memory (RRAM) has been an outstanding candidate among various emerging nonvolatile memories for high-density storage and in-memory computing applications.
Li-Wen Wang, Chih-Wei Huang, Ke-Jing Lee, Sheng-Yuan Chu, Yeong-Her Wang   +4 more
doaj   +1 more source