Aug 2, 2024 · Here we show that in the case of superconducting optoelectronic neurons, it is possible to construct dynamical equations that closely follow the full temporal ...
One challenge related to developing algorithms for spiking neuromorphic hardware is that spikes are discontinuous events, which makes formal analysis difficult.
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The paper presents novel abstract models of probabilistic spiking neuron and neural networks that are inspired by stochastic processes in biological neurons.
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Jun 27, 2022 · Due to the ubiquity of spiking neurons in neuronal processes, various simple spiking neuron models have been proposed as an alternative to ...
In this paper, a simple model that reproduces the rich behavior of biological neurons, including spiking, bursting, and mixed mode firing patters, post- ...
In this paper we investigate how spiking and non-spiking neurons can be combined to create a sensorimotor neuron pathway capable of shaping network output ...
Biological neuron models, also known as spiking neuron models, are mathematical descriptions of the conduction of electrical signals in neurons.
The goal of this review is to introduce different models developed for spiking neural networks and to compare them.
Apr 12, 2024 · We show that neurons with SFA endow networks of spiking neurons with the capability to learn very fast, even without synaptic plasticity.
We review methods for transferring our ability to construct interesting networks that perform relevant tasks from the artificial continuous domain to more ...