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Titel:

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

Dokumenttyp:
Zeitschriftenaufsatz
Autor(en):
Pechmann, Stefan; Mai, Timo; Potschka, Julian; Reiser, Daniel; Reichel, Peter; Breiling, Marco; Reichenbach, Marc; Hagelauer, Amelie
Abstract:
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. This paper introduces a memory block using resistive memory cells (RRAM) to realize this weight and bias storage in an embedded and distributed way while also offering programming and multi-level abil...     »
Zeitschriftentitel:
Micromachines
Jahr:
2021
Band / Volume:
12
Heft / Issue:
11
Volltext / DOI:
doi:10.3390/mi12111277
WWW:
https://www.mdpi.com/2072-666X/12/11/1277
Print-ISSN:
2072-666X
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