arrow
返回

Multi-state MRAM cells for hardware neuromorphic computing

delete2022-05-03
delete29
delete
OA
AI
P
Piotr Rzeszut *
J
Jakub Chęciński
I
Ireneusz Brzozowski
S
Sławomir Ziętek
W
Witold Skowroński
T
T. Stobiecki
DOI:10.1038/s41598-022-11199-4delete
delete原文链接
delete分享
delete收藏
查看原文
摘要

摘要

En 中文
Magnetic tunnel junctions (MTJ) have been successfully applied in various sensing application and digital information storage technologies. Currently, a number of new potential applications of MTJs are being actively studied, including high-frequency electronics, energy harvesting or random number generators. Recently, MTJs have been also proposed in designs of new platforms for unconventional or bio-inspired computing. In the current work, we present a complete hardware implementation design of a neural computing device that incorporates serially connected MTJs forming a multi-state memory cell can be used in a hardware implementation of a neural computing device. The main purpose of the multi-cell is the formation of quantized weights in the network, which can be programmed using the proposed electronic circuit. Multi-cells are connected to a CMOS-based summing amplifier and a sigmoid function generator, forming an artificial neuron. The operation of the designed network is tested using a recognition of hand-written digits in 20 x 20 pixels matrix and shows detection ratio comparable to the software algorithm, using weights stored in a multi-cell consisting of four MTJs or more. Moreover, the presented solution has better energy efficiency in terms of energy consumed per single image processing, as compared to a similar design.
Keyword:
NEURAL-NETWORK
MEMRISTOR
AI总结

AI总结

对已上传原文的论文进行重点信息的提取,主要内容包括:简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。

期刊

Scientific Reports 封面图
Scientific Reports
IF:
3.9
论文数:
27.9W
被引数:
83.5W

机构

A
AGH University of Krakow
学者数:
9.2K
论文数: 9.4K
被引数: 1.2W
引用论文

引用论文

Neural network based optimization approach for energy demand prediction in smart grid
err2018-01-01
err175
PREAI
errMuralitharan, K.; Sakthivel, R.; Vishnuvarthan, R.
err分享
err收藏
err
IF0
err
err0
PREAI
err
err分享
err收藏
Shape anisotropy revisited in single-digit nanometer magnetic tunnel junctions
err2018-02-14
err154
errOAAI
errWatanabe, K.; Jinnai, B.; Fukami, S.; Sato, H.; Ohno, H.
err分享
err收藏
学者 查看更多内容