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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Vydané v:	Advanced intelligent systems Ročník 2; číslo 11
Hlavní autori:	Mehonic, Adnan, Sebastian, Abu, Rajendran, Bipin, Simeone, Osvaldo, Vasilaki, Eleni, Kenyon, Anthony J.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Weinheim John Wiley & Sons, Inc 01.11.2020 Wiley
Predmet:	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
On-line prístup:	Získať plný text
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