A Low-Power RRAM Memory Block for Embedded, Multi-Level Weight and Bias Storage in Artificial Neural Networks

A Low-Power RRAM Memory Block for Embedded, Multi-Level Weight and Bias Storage in Artificial Neural Networks

Pattern recognition as a computing task is very well suited for machine learning algorithms utilizing artificial neural networks (ANNs). Computing systems using ANNs usually require some sort of data storage to store the weights and bias values for the processing elements of the individual neurons....

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Bibliographic Details
Main Authors: Stefan Pechmann, Timo Mai, Julian Potschka, Daniel Reiser, Peter Reichel, Marco Breiling, Marc Reichenbach, Amelie Hagelauer
Format: article
Language:EN
Published: MDPI AG 2021
Subjects:
ANN
low-power
embedded memory
memory block
multi-level
RRAM
Mechanical engineering and machinery
TJ1-1570
Online Access:https://doaj.org/article/562cb5742c42492f993e25ce25091a4c
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https://doaj.org/article/562cb5742c42492f993e25ce25091a4c

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