Adaptive extreme edge computing for wearable devices

E Covi, E Donati, X Liang, D Kappel… - Frontiers in …, 2021 - frontiersin.org
Wearable devices are a fast-growing technology with impact on personal healthcare for both
society and economy. Due to the widespread of sensors in pervasive and distributed …

Spiking neural network integrated circuits: A review of trends and future directions

A Basu, L Deng, C Frenkel… - 2022 IEEE Custom …, 2022 - ieeexplore.ieee.org
The rapid growth of deep learning, spurred by its successes in various fields ranging from
face recognition [1] to game playing [2], has also triggered a growing interest in the design of …

The BrainScaleS-2 accelerated neuromorphic system with hybrid plasticity

C Pehle, S Billaudelle, B Cramer, J Kaiser… - Frontiers in …, 2022 - frontiersin.org
Since the beginning of information processing by electronic components, the nervous
system has served as a metaphor for the organization of computational primitives. Brain …

Hardware implementation of deep network accelerators towards healthcare and biomedical applications

MR Azghadi, C Lammie, JK Eshraghian… - … Circuits and Systems, 2020 - ieeexplore.ieee.org
The advent of dedicated Deep Learning (DL) accelerators and neuromorphic processors
has brought on new opportunities for applying both Deep and Spiking Neural Network …

SAM: a unified self-adaptive multicompartmental spiking neuron model for learning with working memory

S Yang, T Gao, J Wang, B Deng, MR Azghadi… - Frontiers in …, 2022 - frontiersin.org
Working memory is a fundamental feature of biological brains for perception, cognition, and
learning. In addition, learning with working memory, which has been show in conventional …

Hand-gesture recognition based on EMG and event-based camera sensor fusion: A benchmark in neuromorphic computing

E Ceolini, C Frenkel, SB Shrestha, G Taverni… - Frontiers in …, 2020 - frontiersin.org
Hand gestures are a form of non-verbal communication used by individuals in conjunction
with speech to communicate. Nowadays, with the increasing use of technology, hand …

A survey on deep learning hardware accelerators for heterogeneous hpc platforms

C Silvano, D Ielmini, F Ferrandi, L Fiorin… - arxiv preprint arxiv …, 2023 - arxiv.org
Recent trends in deep learning (DL) imposed hardware accelerators as the most viable
solution for several classes of high-performance computing (HPC) applications such as …

Brain-inspired computing: A systematic survey and future trends

G Li, L Deng, H Tang, G Pan, Y Tian… - Proceedings of the …, 2024 - ieeexplore.ieee.org
Brain-inspired computing (BIC) is an emerging research field that aims to build fundamental
theories, models, hardware architectures, and application systems toward more general …

Self-organization of an inhomogeneous memristive hardware for sequence learning

M Payvand, F Moro, K Nomura, T Dalgaty… - Nature …, 2022 - nature.com
Learning is a fundamental component of creating intelligent machines. Biological
intelligence orchestrates synaptic and neuronal learning at multiple time scales to self …

Surrogate gradients for analog neuromorphic computing

B Cramer, S Billaudelle, S Kanya… - Proceedings of the …, 2022 - National Acad Sciences
To rapidly process temporal information at a low metabolic cost, biological neurons integrate
inputs as an analog sum, but communicate with spikes, binary events in time. Analog …