Memristive Hodgkin-Huxley Spiking Neuron Model for Reproducing Neuron Behaviors [PDF]
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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Memristive Izhikevich Spiking Neuron Model and Its Application in Oscillatory Associative Memory [PDF]
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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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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Memristive LIF Spiking Neuron Model and Its Application in Morse Code [PDF]
Frontiers in Neuroscience, 2022 The leaky integrate-and-fire (LIF) spiking model can successively mimic the firing patterns and information propagation of a biological neuron. It has been applied in neural networks, cognitive computing, and brain-inspired computing.
Xiaoyan Fang +3 more
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Artificial optoelectronic spiking neuron based on a resonant tunnelling diode coupled to a vertical cavity surface emitting laser [PDF]
Nanophotonics, 2022 Excitable optoelectronic devices represent one of the key building blocks for implementation of artificial spiking neurons in neuromorphic (brain-inspired) photonic systems.
Hejda Matěj +11 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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Spiking Neuron with Sensing Coil Based on a Volatile Memristor [PDF]
SensorsThe convergence of sensing and processing is a critical frontier in the development of energy-efficient spiking edge intelligence. This paper presents a novel hardware implementation of a sensory neuron evolving from the leaky integrate-and-fire (LIF ...
Timur Karimov +5 more
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Spiking neuron network Helmholtz machine. [PDF]
Front Comput Neurosci, 2015 An increasing amount of behavioral and neurophysiological data suggests that the brain performs optimal (or near-optimal) probabilistic inference and learning during perception and other tasks. Although many machine learning algorithms exist that perform inference and learning in an optimal way, the complete description of how one of those algorithms ...
Sountsov P, Miller P.
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A memristive spiking neuron with firing rate coding [PDF]
Frontiers in Neuroscience, 2015 Perception, decisions, and sensations are all encoded into trains of action potentials in the brain. The relation between stimulus strength and all-or-nothing spiking of neurons is widely believed to be the basis of this coding.
Marina eIgnatov +4 more
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Development of digital hardware for a spiking image recognition network employing a novel burst-based reinforcement learning approach [PDF]
Scientific ReportsThe primary focus of accurate and cost-effective computation in machines endowed with advanced cognitive abilities is to enhance the accuracy and speed of learning in the bio-inspired spiking machine vision networks.
Soheila Nazari, Masoud Amiri
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