IEEE transactions on biomedical circuits and systems
May 15, 2019
This paper introduces a novel electroencephalogram (EEG) data classification scheme together with its implementation in hardware using an innovative approach. The proposed scheme integrates into a single, end-to-end trainable model a spatial filterin...
IEEE transactions on biomedical circuits and systems
Mar 27, 2019
Advances in neuroscience uncover the mechanisms employed by the brain to efficiently solve complex learning tasks with very limited resources. However, the efficiency is often lost when one tries to port these findings to a silicon substrate, since b...
IEEE transactions on biomedical circuits and systems
Jan 10, 2019
Advancements in wireless sensor network technologies have enabled the proliferation of miniaturized body-worn sensors, capable of long-term pervasive biomedical signal monitoring. Remote cardiovascular monitoring has been one of the beneficiaries of ...
IEEE transactions on biomedical circuits and systems
Nov 9, 2018
Shifting computing architectures from von Neumann to event-based spiking neural networks (SNNs) uncovers new opportunities for low-power processing of sensory data in applications such as vision or sensorimotor control. Exploring roads toward cogniti...
IEEE transactions on biomedical circuits and systems
Sep 10, 2018
The human brain is composed of 10 neurons with a switching speed of about 1 ms. Studying spiking neural networks, including the modeling, simulation, and implementation of the biological neuron models, helps us to learn about the brain and the relate...
IEEE transactions on biomedical circuits and systems
Aug 27, 2018
Recently, a great deal of scientific endeavour has been devoted to developing spin-based neuromorphic platforms owing to the ultra-low-power benefits offered by spin devices and the inherent correspondence between spintronic phenomena and the desired...
IEEE transactions on biomedical circuits and systems
Jul 16, 2018
The stochastic neuron is a key for event-based probabilistic neural networks. We propose a stochastic neuron using a metal-oxide resistive random-access memory (ReRAM). The ReRAM's conducting filament with built-in stochasticity is used to mimic the ...
IEEE transactions on biomedical circuits and systems
Jun 19, 2018
This paper describes a fully spike-based neural network for optical flow estimation from dynamic vision sensor data. A low power embedded implementation of the method, which combines the asynchronous time-based image sensor with IBM's TrueNorth Neuro...
IEEE transactions on biomedical circuits and systems
Jun 12, 2018
Vision processing with dynamic vision sensors (DVSs) is becoming increasingly popular. This type of a bio-inspired vision sensor does not record static images. The DVS pixel activity relies on the changes in light intensity. In this paper, we introdu...
IEEE transactions on biomedical circuits and systems
May 24, 2018
Spiking neural networks (SNNs) are being explored in an attempt to mimic brain's capability to learn and recognize at low power. Crossbar architecture with highly scalable resistive RAM or RRAM array serving as synaptic weights and neuronal drivers i...