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A Compact Fully Ferroelectric-FETs Reservoir Computing Network With Sub-100 ns Operating Speed.

Authors :
Tang, Mingfeng
Zhan, Xuepeng
Wu, Shuhao
Bai, Maoying
Feng, Yang
Zhao, Guoqing
Wu, Jixuan
Chai, Junshuai
Xu, Hao
Wang, Xiaolei
Chen, Jiezhi
Source :
IEEE Electron Device Letters; Sep2022, Vol. 43 Issue 9, p1555-1558, 4p
Publication Year :
2022

Abstract

Reservoir computing (RC) is a low-cost and temporary-signal friendly computational framework, whose hardware implementation is hindered by integrating huge amounts and various kinds of devices. Benefitted from the logic in memory (LIM) capability, the process compatible Hf0.5Zr0.5O2 (HZO)-based ferroelectric field-effect-transistor (FeFET) is a promising candidate for implementing artificial networks. In this letter, a fully FeFETs RC network is proposed. Multiple functions can be achieved in a single device owing to its intrinsic characteristics, and the richness of virtual nodes is largely enhanced through full-connection structures. Impressively, only 44 FeFETs are required to construct a compact RC network with 100 ns operating speed and high accuracy in classification tasks. This paves the way to develop the high energy-efficiency FeFET RC networks. [ABSTRACT FROM AUTHOR]

Subjects

Subjects :
SPEED
TASK analysis

Details

Language :
English
ISSN :
07413106
Volume :
43
Issue :
9
Database :
Complementary Index
Journal :
IEEE Electron Device Letters
Publication Type :
Academic Journal
Accession number :
158869229
Full Text :
https://doi.org/10.1109/LED.2022.3188496