Robust neuromorphic coupled oscillators for adaptive pacemakers
Neural coupled oscillators are a useful building block in numerous models and applications.
They were analyzed extensively in theoretical studies and more recently in biologically …
They were analyzed extensively in theoretical studies and more recently in biologically …
Neuromorphic pattern generation circuits for bioelectronic medicine
Chronic diseases can greatly benefit from bio-electronic medicine approaches.
Neuromorphic electronic circuits present ideal characteristics for the development of brain …
Neuromorphic electronic circuits present ideal characteristics for the development of brain …
Supervised training of spiking neural networks for robust deployment on mixed-signal neuromorphic processors
Mixed-signal analog/digital circuits emulate spiking neurons and synapses with extremely
high energy efficiency, an approach known as “neuromorphic engineering”. However …
high energy efficiency, an approach known as “neuromorphic engineering”. However …
Neuromorphic networks using nonlinear mixed-feedback multi-timescale bio-mimetic neurons
Biological neurons exhibit rich and complex nonlinear dynamics, which are computationally
expensive and power-hungry for hardware implementation. This paper demonstrates the …
expensive and power-hungry for hardware implementation. This paper demonstrates the …
Extending the neural engineering framework for nonideal silicon synapses
The Neural Engineering Framework (NEF) is a theory for mapping computations onto
biologically plausible networks of spiking neurons. This theory has been applied to a …
biologically plausible networks of spiking neurons. This theory has been applied to a …
Programmable neuromorphic circuits for spike-based neural dynamics
Hardware implementations of spiking neural networks offer promising solutions for a wide
set of tasks, ranging from autonomous robotics to brain machine interfaces. We propose a …
set of tasks, ranging from autonomous robotics to brain machine interfaces. We propose a …
Implementation and characterization of mixed-signal neuromorphic ASICs
A Hartel - 2016 - archiv.ub.uni-heidelberg.de
Accelerated neuromorphic hardware allows the emulation of spiking neural networks with a
high speed-up factor compared to classical computer simulation approaches. However …
high speed-up factor compared to classical computer simulation approaches. However …
A comprehensive workflow for general-purpose neural modeling with highly configurable neuromorphic hardware systems
D Brüderle, MA Petrovici, B Vogginger, M Ehrlich… - Biological …, 2011 - Springer
In this article, we present a methodological framework that meets novel requirements
emerging from upcoming types of accelerated and highly configurable neuromorphic …
emerging from upcoming types of accelerated and highly configurable neuromorphic …
Neuromorphic dynamical synapses with reconfigurable voltage-gated kinetics
J Wang, G Cauwenberghs… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
Objective: Although biological synapses express a large variety of receptors in neuronal
membranes, the current hardware implementation of neuromorphic synapses often rely on …
membranes, the current hardware implementation of neuromorphic synapses often rely on …
Feed-forward and recurrent inhibition for compressing and classifying high dynamic range biosignals in spiking neural network architectures
R Sava, E Donati, G Indiveri - 2023 IEEE Biomedical Circuits …, 2023 - ieeexplore.ieee.org
Neuromorphic processors that implement Spiking Neural Networks (SNNs) using mixed-
signal analog/digital circuits represent a promising technology for closed-loop real-time …
signal analog/digital circuits represent a promising technology for closed-loop real-time …