In-memory and in-sensor reservoir computing with memristive devices
Work
Year: 2024
Type: article
Abstract: Despite the significant progress made in deep learning on digital computers, their energy consumption and computational speed still fall short of meeting the standards for brain-like computing. To add... more
Source: APL Machine Learning
Institutions University of Hong Kong, Hong Kong University of Science and Technology, University of Southern California, Syracuse University
Cites: 102
Cited by: 11
Related to: 10
FWCI: 6.723
Citation percentile (by year/subfield): 100
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Sustainable Development Goal Affordable and clean energy
Open Access status: diamond