In individuals with sensory-motor impairments, missing limb functions can be restored using
neuroprosthetic devices that directly interface with the nervous system. However, restoring …

Despite the success of Deep Neural Networks—a type of Artificial Neural Network (ANN)—in
problem domains such as image recognition and speech processing, the energy and …

Reconfigurable field effect transistors are an emerging class of electronic devices, which
exploit a structure with multiple independent gates to selectively adjust the charge carrier …

Recent years have witnessed a growing interest in EEG-based wearable classifiers of
emotions, which could enable the real-time monitoring of patients suffering from …

This paper introduces the processing element architecture of the second generation
SpiNNaker chip, implemented in 22nm FDSOI. On circuit level, the chip features adaptive …

We implemented two neural network based benchmark tasks on a prototype chip of the
second-generation SpiNNaker (SpiNNaker 2) neuromorphic system: keyword spotting and …

With the advent of high-density micro-electrodes arrays, developing neural probes satisfying
the real-time and stringent power-efficiency requirements becomes more challenging. A …

This paper presents an approach to design analog building blocks for nanometer systems
on a chip (SoCs) that are based on digital standard-cells. The proposed approach …

Introduction Multi-channel electrophysiology systems for recording of neuronal activity face
significant data throughput limitations, hampering real-time, data-informed experiments …

In this paper, we propose a novel standard-cell-based OTA architecture based on an
improved version of the differential to single-ended converter, previously proposed by the …