Adaptive extreme edge computing for wearable devices
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 …
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
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 …
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
Since the beginning of information processing by electronic components, the nervous
system has served as a metaphor for the organization of computational primitives. Brain …
system has served as a metaphor for the organization of computational primitives. Brain …
Hardware implementation of deep network accelerators towards healthcare and biomedical applications
The advent of dedicated Deep Learning (DL) accelerators and neuromorphic processors
has brought on new opportunities for applying both Deep and Spiking Neural Network …
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
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 …
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
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 …
with speech to communicate. Nowadays, with the increasing use of technology, hand …
A survey on deep learning hardware accelerators for heterogeneous hpc platforms
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 …
solution for several classes of high-performance computing (HPC) applications such as …
Brain-inspired computing: A systematic survey and future trends
Brain-inspired computing (BIC) is an emerging research field that aims to build fundamental
theories, models, hardware architectures, and application systems toward more general …
theories, models, hardware architectures, and application systems toward more general …
Self-organization of an inhomogeneous memristive hardware for sequence learning
Learning is a fundamental component of creating intelligent machines. Biological
intelligence orchestrates synaptic and neuronal learning at multiple time scales to self …
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 …
inputs as an analog sum, but communicate with spikes, binary events in time. Analog …