[HTML][HTML] Neuromorphic artificial intelligence systems

D Ivanov, A Chezhegov, D Larionov - Frontiers in Neuroscience, 2022‏ - frontiersin.org
Modern artificial intelligence (AI) systems, based on von Neumann architecture and classical
neural networks, have a number of fundamental limitations in comparison with the …

Large-scale neuromorphic spiking array processors: A quest to mimic the brain

CS Thakur, JL Molin, G Cauwenberghs… - Frontiers in …, 2018‏ - frontiersin.org
Neuromorphic engineering (NE) encompasses a diverse range of approaches to information
processing that are inspired by neurobiological systems, and this feature distinguishes …

Deep neural network for respiratory sound classification in wearable devices enabled by patient specific model tuning

J Acharya, A Basu - IEEE transactions on biomedical circuits …, 2020‏ - ieeexplore.ieee.org
The primary objective of this paper is to build classification models and strategies to identify
breathing sound anomalies (wheeze, crackle) for automated diagnosis of respiratory and …

Spiking neural networks hardware implementations and challenges: A survey

M Bouvier, A Valentian, T Mesquida… - ACM Journal on …, 2019‏ - dl.acm.org
Neuromorphic computing is henceforth a major research field for both academic and
industrial actors. As opposed to Von Neumann machines, brain-inspired processors aim at …

White paper on critical and massive machine type communication towards 6G

NH Mahmood, S Böcker, A Munari, F Clazzer… - arxiv preprint arxiv …, 2020‏ - arxiv.org
The society as a whole, and many vertical sectors in particular, is becoming increasingly
digitalized. Machine Type Communication (MTC), encompassing its massive and critical …

Machine type communications: Key drivers and enablers towards the 6G era

NH Mahmood, S Böcker, I Moerman, OA López… - EURASIP Journal on …, 2021‏ - Springer
The recently introduced 5G New Radio is the first wireless standard natively designed to
support critical and massive machine type communications (MTC). However, it is already …

Integrating visual perception with decision making in neuromorphic fault-tolerant quadruplet-spike learning framework

S Yang, H Wang, Y Pang, Y **… - IEEE Transactions on …, 2023‏ - ieeexplore.ieee.org
The brain possesses the remarkable ability to seamlessly integrate perception with decision
making within a dynamically changing environment in a fault-tolerant, end-to-end manner …

A fast and energy-efficient SNN processor with adaptive clock/event-driven computation scheme and online learning

S Li, Z Zhang, R Mao, J **ao, L Chang… - IEEE Transactions on …, 2021‏ - ieeexplore.ieee.org
In the recent years, the spiking neural network (SNN) has attracted increasing attention due
to its low energy consumption and online learning potential. However, the design of SNN …

Spiking neural network for ultralow-latency and high-accurate object detection

J Qu, Z Gao, T Zhang, Y Lu, H Tang… - IEEE Transactions on …, 2024‏ - ieeexplore.ieee.org
Spiking Neural Networks (SNNs) have attracted significant attention for their energy-efficient
and brain-inspired event-driven properties. Recent advancements, notably Spiking-YOLO …

A survey of neuromorphic computing-in-memory: Architectures, simulators, and security

F Staudigl, F Merchant, R Leupers - IEEE Design & Test, 2021‏ - ieeexplore.ieee.org
This work is a survey of neuromorphic computing-in-memory. Unlike existing surveys that
focus on hardware or application-level perspectives, the authors elaborate on architectures …