Memristors—From In‐Memory Computing, Deep Learning Acceleration, and Spiking Neural Networks to the Future of Neuromorphic and Bio‐Inspired Computing

Machine learning, particularly in the form of deep learning (DL), has driven most of the recent fundamental developments in artificial intelligence (AI). DL is based on computational models that are, to a certain extent, bio‐inspired, as they rely on networks of connected simple computing units oper...

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Bibliographic Details
Published in:	Advanced intelligent systems Vol. 2; no. 11
Main Authors:	Mehonic, Adnan, Sebastian, Abu, Rajendran, Bipin, Simeone, Osvaldo, Vasilaki, Eleni, Kenyon, Anthony J.
Format:	Journal Article
Language:	English
Published:	Weinheim John Wiley & Sons, Inc 01.11.2020 Wiley
Subjects:	Algorithms Architecture Artificial intelligence Biomimetics CMOS Computer memory Deep learning Digital switching Electrodes in-memory computing Machine learning Memory Memristors Moore's law Neural networks neuromorphic systems Phase transitions power-efficient artificial intelligence Spiking spiking neural networks Technological change
ISSN:	2640-4567, 2640-4567
Online Access:	Get full text
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