logo
ResearchBunny Logo
Abstract
This paper presents a hybrid architecture for edge computing, combining a 2D memristor crossbar array with CMOS circuitry to implement the extreme learning machine (ELM) algorithm. A hexagonal boron nitride (h-BN) based memristor crossbar array acts as the decoder, while a CMOS circuit functions as the encoder. The hybrid architecture demonstrates effective performance on complex audio, image, and other non-linear classification tasks using real-time datasets.
Publisher
npj 2D Materials and Applications
Published On
Jan 21, 2022
Authors
Pratik Kumar, Kaichen Zhu, Xu Gao, Sui-Dong Wang, Mario Lanza, Chetan Singh Thakur
Tags
edge computing
memristor crossbar
CMOS circuitry
extreme learning machine
non-linear classification
real-time datasets
hybrid architecture

Related Publications

Explore these studies to deepen your understanding of the subject.

Two-dimensional and high-order directional information modulations for secure communications based on programmable metasurface
Engineering and Technology

Two-dimensional and high-order directional information modulations for secure communications based on programmable metasurface

H. Xu, J. W. Wu, et al.

Deep-learning-based image segmentation integrated with optical microscopy for automatically searching for two-dimensional materials
Engineering and Technology

Deep-learning-based image segmentation integrated with optical microscopy for automatically searching for two-dimensional materials

S. Masubuchi, E. Watanabe, et al.

Toward optical coherence tomography on a chip: in vivo three-dimensional human retinal imaging using photonic integrated circuit-based arrayed waveguide gratings
Medicine and Health

Toward optical coherence tomography on a chip: in vivo three-dimensional human retinal imaging using photonic integrated circuit-based arrayed waveguide gratings

E. A. Rank, R. Sentosa, et al.

Powering AI at the edge: A robust, memristor-based binarized neural network with near-memory computing and miniaturized solar cell
Engineering and Technology

Powering AI at the edge: A robust, memristor-based binarized neural network with near-memory computing and miniaturized solar cell

F. Jebali, A. Majumdar, et al.

Listen, Learn & Level Up
Over 10,000 hours of research content in 25+ fields, available in 12+ languages.
No more digging through PDFs—just hit play and absorb the world's latest research in your language, on your time.
listen to research audio papers with researchbunny