This article presents a bioinspired, event-driven neuromorphic sensing system (NSS)
capable of performing on-chip feature extraction and “send-on-delta” pulse-based …

With recent advances in learning algorithms, recurrent networks of spiking neurons are
achieving performance that is competitive with vanilla recurrent neural networks. However …

The adaptive leaky integrate-and-fire (ALIF) model is fundamental within computational
neuroscience and has been instrumental in studying our brains $\textit {in silico} $. Due to …

Neuromorphic near-sensor computing has recently emerged as a low-power and low-
memory paradigm for the design of artificial intelligence (AI)-enabled IoT devices working at …

This paper proposes a novel event-driven level-crossing ADC (LCADC) that highly improves
power efficiency and accuracy compared to existing LCADC implementations. For …

A digital-impulse galvanic coupling as a new high-speed trans-dural (from cortex to the
skull) data transmission method has been presented in this article. The proposed wireless …

The event-driven and sparse nature of communication between spiking neurons in the brain
holds great promise for flexible and energy-efficient AI. Recent advances in learning …

In this paper, a comprehensive exploration is undertaken to elucidate the utilization of
Spiking Neural Networks (SNNs) within the biomedical domain. The investigation delves …

Level-crossing analog-to-digital converters (LC-ADCs) are neuromorphic, event-driven data
converters that are gaining much attention for resource-constrained applications where …

Fine-grain tactile sensing has recently gained much attention in robotics applications where
the manipulation of potentially fragile objects must be provided. This has led to the …