Solid-State Oxide-Ion Synaptic Transistor for Neuromorphic Computing

• Published in: arXiv.org
• Main Authors: Langner, Philipp, Chiabrera, Francesco, Alayo, Nerea, Nizet, Paul, Morrone, Luigi, Bozal-Ginesta, Carlota, Morata, Alex, Tarancòn, Albert
• Format: Paper
• Language: English
• Published: Ithaca Cornell University Library, arXiv.org 01.08.2024
• Subjects: Artificial intelligence; Artificial neural networks; Biological computing; Biological properties; Commercialization; Energy consumption; Handwriting recognition; Memory devices; Neural networks; Neuromorphic computing; Solid state; Synapses; Transistors

Neuromorphic hardware facilitates rapid and energy-efficient training and operation of neural network models for artificial intelligence. However, existing analog in-memory computing devices, like memristors, continue to face significant challenges that impede their commercialization. These challeng...