Artificial intelligence (AI), the technique of extracting information from complex database
using sophisticated computer algorithms, has incorporated itself in medical field. AI …

Brain-inspired computing uses insights from neuroscience to develop more efficient
computing systems. The approach is of use in a broad range of applications—from neural …

Neuromorphic computing implementing spiking neural networks (SNN) is a promising
technology for reducing the footprint of optical transceivers, as required by the fast-paced …

Neuromorphic systems require user-friendly software to support the design and optimization
of experiments. In this work, we address this need by presenting our development of a …

A spiking neural network (SNN) nonlinear equalizer model is implemented on the mixed-
signal neuromorphic hardware system BrainScaleS-2 and evaluated for an IM/DD link. The …

Spiking Neural Network Linear Equalization: Experimental Demonstration of 2km 100Gb/s IM/DD
PAM4 Optical Transmission Page 1 Spiking Neural Network Linear Equalization: Experimental …

Neuromorphic systems aim to provide accelerated low-power simulation of Spiking Neural
Networks (SNNs), typically featuring simple and efficient neuron models such as the Leaky …

A fruitful approach towards neuromorphic computing is to mimic mechanisms of the brain in
physical devices, which has led to successful replication of neuronlike dynamics and …

Traditional neuromorphic hardware architectures rely on event-driven computation, where
the asynchronous transmission of events, such as spikes, triggers local computations within …