Dynamic resistive switching devices for neuromorphic computing

Y Wu, X Wang, WD Lu - Semiconductor Science and Technology, 2021‏ - iopscience.iop.org
Neuromorphic systems that can emulate the structure and the operations of biological neural
circuits have long been viewed as a promising hardware solution to meet the ever-growing …

Exploiting non-idealities of resistive switching memories for efficient machine learning

V Yon, A Amirsoleimani, F Alibart, RG Melko… - Frontiers in …, 2022‏ - frontiersin.org
Novel computing architectures based on resistive switching memories (also known as
memristors or RRAMs) have been shown to be promising approaches for tackling the …

Advances in neuromorphic spin-based spiking neural networks: a review

G Verma, N Bindal, A Nisar, S Dhull… - IEEE Nanotechnology …, 2021‏ - ieeexplore.ieee.org
This article reviews the recent developments and challenges in spintronic based spiking
neural networks (SNNs). The present CPUs and GPUs are powerful tools that are capable of …

Fault Analysis for a MTJ-based Spiking Neural Network

L Miceli, I Vatajelu, V Champac - 25th IEEE Latin American Test …, 2024‏ - hal.science
Interest in Spiking Neural Networks (SNN), which mirror brain functionality, within the
Artificial Intelligence (AI) domain stems from their potential for energy efficiency. Recent …

Diseño y confiabilidad de sistemas de computación neuromórfica

LM Lara - 2023‏ - inaoe.repositorioinstitucional.mx
La Inteligencia Artificial (IA) es un campo de la informática que persigue realizar tareas que
tienen atributos de inteligencia humana, como pueden ser el aprendizaje, el razonamiento y …

[معلومات الإصدار][C] Advances in Neuromorphic Spin-Based Spiking Neural Networks

G VERMA, N BINDAL, A NISAR, S DHULL…