Neuromorphic hardware for somatosensory neuroprostheses
In individuals with sensory-motor impairments, missing limb functions can be restored using
neuroprosthetic devices that directly interface with the nervous system. However, restoring …
neuroprosthetic devices that directly interface with the nervous system. However, restoring …
Neuromorphic intermediate representation: A unified instruction set for interoperable brain-inspired computing
Spiking neural networks and neuromorphic hardware platforms that simulate neuronal
dynamics are getting wide attention and are being applied to many relevant problems using …
dynamics are getting wide attention and are being applied to many relevant problems using …
Spike encoding techniques for IoT time-varying signals benchmarked on a neuromorphic classification task
Spiking Neural Networks (SNNs), known for their potential to enable low energy
consumption and computational cost, can bring significant advantages to the realm of …
consumption and computational cost, can bring significant advantages to the realm of …
Computing of neuromorphic materials: an emerging approach for bioengineering solutions
The potential of neuromorphic computing to bring about revolutionary advancements in
multiple disciplines, such as artificial intelligence (AI), robotics, neurology, and cognitive …
multiple disciplines, such as artificial intelligence (AI), robotics, neurology, and cognitive …
The intel neuromorphic DNS challenge
A critical enabler for progress in neuromorphic computing research is the ability to
transparently evaluate different neuromorphic solutions on important tasks and to compare …
transparently evaluate different neuromorphic solutions on important tasks and to compare …
Impact of spiking neurons leakages and network recurrences on event-based spatio-temporal pattern recognition
Spiking neural networks coupled with neuromorphic hardware and event-based sensors are
getting increased interest for low-latency and low-power inference at the edge. However …
getting increased interest for low-latency and low-power inference at the edge. However …
ETLP: Event-based three-factor local plasticity for online learning with neuromorphic hardware
Neuromorphic perception with event-based sensors, asynchronous hardware, and spiking
neurons shows promise for real-time, energy-efficient inference in embedded systems. Brain …
neurons shows promise for real-time, energy-efficient inference in embedded systems. Brain …
SHIP: a computational framework for simulating and validating novel technologies in hardware spiking neural networks
Investigations in the field of spiking neural networks (SNNs) encompass diverse, yet
overlap**, scientific disciplines. Examples range from purely neuroscientific …
overlap**, scientific disciplines. Examples range from purely neuroscientific …
Low-power event-based face detection with asynchronous neuromorphic hardware
C Caccavella, F Paredes-Vallés… - … Joint Conference on …, 2024 - ieeexplore.ieee.org
The rise of mobility, IoT and wearables has shifted processing to the edge of the sensors,
driven by the need to reduce latency, communication costs and overall energy consumption …
driven by the need to reduce latency, communication costs and overall energy consumption …
Critically synchronized brain waves form an effective, robust and flexible basis for human memory and learning
VL Galinsky, LR Frank - Scientific Reports, 2023 - nature.com
The effectiveness, robustness, and flexibility of memory and learning constitute the very
essence of human natural intelligence, cognition, and consciousness. However, currently …
essence of human natural intelligence, cognition, and consciousness. However, currently …