Results 11 to 20 of about 36,106 (159)
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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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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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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, 2006 Simulating large networks of spiking neurons is a very common task in the areas of Neuroinformatics and Computational Neurosciences. These simulations are time-consuming but also often intrinsically parallel. The recent advent of powerful and programmable graphic cards seems to be a pertinent solution to the problem: they offer a cheap but efficient ...
Fabrice Bernhard, Renaud Keriven
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