Results 11 to 20 of about 215,411 (303)
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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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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Self-Reset Schemes for Magnetic Domain Wall-Based Neuron
IEEE Journal on Exploratory Solid-State Computational Devices and Circuits, 2022 Spintronic artificial spiking neurons are promising due to their ability to closely mimic the leaky integrate-and-fire (LIF) dynamics of the biological LIF spiking neuron. However, the neuron needs to be reset after firing.
Debasis Das, Xuanyao Fong
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Checkpoints for Parallel-Spiking-Neuron
, 2023 https://github.com/fangwei123456/Parallel-Spiking ...
Wei Fang (9080993)
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Transfer Learning Algorithm and Software Framework Based on Spiking Neuron Network [PDF]
Jisuanji gongcheng, 2020 Spiking Neuron Network(SNN) uses spike sequence for data processing,so it has the excellent characteristic of low power consumption.However,due to the immaturity of learning algorithm,the multilayer network training has difficulty in convergence ...
SHANG Yingjie, DONG Liya, HE Hu
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Extending the Functional Subnetwork Approach to a Generalized Linear Integrate-and-Fire Neuron Model
Frontiers in Neurorobotics, 2020 Engineering neural networks to perform specific tasks often represents a monumental challenge in determining network architecture and parameter values.
Nicholas S. Szczecinski +2 more
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Building Logistic Spiking Neuron Models Using Analytical Approach
IEEE Access, 2019 Spiking neuron models are inspired by biological neurons. They can simulate the neuronal activities of the mammalian brains, such as spiking (integrator) and periodic oscillation (resonator).
Lei Zhang
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Architecture and Design of a Spiking Neuron Processor Core Towards the Design of a Large-scale Event-Driven 3D-NoC-based Neuromorphic Processor [PDF]
SHS Web of Conferences, 2020 Neuromorphic computing tries to model in hardware the biological brain which is adept at operating in a rapid, real-time, parallel, low power, adaptive and fault-tolerant manner within a volume of 2 liters.
Ogbodo Mark +3 more
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