Results 1 to 10 of about 40,450 (124)
Parameter estimation of neuron models using in-vitro and in-vivo electrophysiological data [PDF]
Frontiers in Neuroinformatics, 2015 Spiking neuron models can accurately predict the response of neurons to somatically injected currents if the model parameters are carefully tuned. Predicting the response of in-vivo neurons responding to natural stimuli presents a far more challenging ...
Eoin Patrick Lynch +2 more
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An artificial spiking quantum neuron [PDF]
npj Quantum Information, 2021 Artificial spiking neural networks have found applications in areas where the temporal nature of activation offers an advantage, such as time series prediction and signal processing.
Lasse Bjørn Kristensen +4 more
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Memristive Izhikevich Spiking Neuron Model and Its Application in Oscillatory Associative Memory
Frontiers in Neuroscience, 2022 The Izhikevich (IZH) spiking neuron model can display spiking and bursting behaviors of neurons. Based on the switching property and bio-plausibility of the memristor, the memristive Izhikevich (MIZH) spiking neuron model is built.
Xiaoyan Fang, Shukai Duan, Lidan Wang
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Modeling and simulation of coupled CBEM spiking neuron model
Xi'an Gongcheng Daxue xuebao, 2021 The CBEM spiking neuron model establishes a new connection between the statistics of neural coding and the biophysical model. In order to narrow the gap between the CBEM model and the biophysical model, a coupled CBEM spike neuron model is proposed.
Jiaying ZHANG, Xingshi HE, Qinglin YU
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Memristive Hodgkin-Huxley Spiking Neuron Model for Reproducing Neuron Behaviors
Frontiers in Neuroscience, 2021 The Hodgkin-Huxley (HH) spiking neuron model reproduces the dynamic characteristics of the neuron by mimicking the action potential, ionic channels, and spiking behaviors. The memristor is a nonlinear device with variable resistance.
Xiaoyan Fang +8 more
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Integrating Non-spiking Interneurons in Spiking Neural Networks
Frontiers in Neuroscience, 2021 Researchers working with neural networks have historically focused on either non-spiking neurons tractable for running on computers or more biologically plausible spiking neurons typically requiring special hardware.
Beck Strohmer +3 more
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All optical Q-switched laser based spiking neuron
Frontiers in Physics, 2022 This paper studies theoretically the use of a Q-switch laser with side light injection as a spiking all-optical neuron for photonic spiking neural networks (PSNN). Ordinary differential equations for the multi-section laser are presented, including terms
Keshia Mekemeza-Ona +2 more
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Progress and Benchmark of Spiking Neuron Devices and Circuits
Advanced Intelligent Systems, 2021 The sustainability of ever more sophisticated artificial intelligence relies on the continual development of highly energy‐efficient and compact computing hardware that mimics the biological neural networks.
Fu-Xiang Liang +2 more
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IEEE Access, 2021 In this first of two closely related papers, we set the foundation for a new framework, called Response Surfaces (RSs), to address fundamental problems of analyzing, designing, and visualizing spiking neurons and networks.
Fatemeh Koohestan-Mahalian +3 more
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Compartmental spiking neuron model CSNM [PDF]
Известия высших учебных заведений: Прикладная нелинейная динамика, 2022 The purpose of this work is to develop a compartment spiking neuron model as an element of growing neural networks. Methods. As part of the work, the CSNM is compared with the Leaky Integrate-and-Fire model by comparing the reactions of point models to a
Bakhshiev, Aleksandr Valeryevich +1 more
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