Mott insulators: A large class of materials for Leaky Integrate and Fire (LIF) artificial neuron
Sign Up to like & getrecommendations! Published in 2018 at "Journal of Applied Physics"
DOI: 10.1063/1.5042756
Abstract: A major challenge in the field of neurocomputing is to mimic the brain's behavior by implementing artificial synapses and neurons directly in hardware. Toward that purpose, many researchers are exploring the potential of new materials… read more here.
Keywords: mott; fire lif; leaky integrate; lif artificial ... See more keywords
Superconducting neural networks with disordered Josephson junction array synaptic networks and leaky integrate-and-fire loop neurons
Sign Up to like & getrecommendations! Published in 2021 at "Journal of Applied Physics"
DOI: 10.1063/5.0027997
Abstract: Fully coupled randomly disordered recurrent superconducting networks with additional open-ended channels for inputs and outputs are considered the basis to introduce a new architecture to neuromorphic computing in this work. Various building blocks of such… read more here.
Keywords: network; neural networks; leaky integrate; synaptic networks ... See more keywords
Mechanisms for bump state localization in two-dimensional networks of leaky integrate-and-fire neurons.
Sign Up to like & getrecommendations! Published in 2024 at "Chaos"
DOI: 10.1063/5.0244833
Abstract: Networks of nonlocally coupled leaky integrate-and-fire neurons exhibit a variety of complex collective behaviors, such as partial synchronization, frequency or amplitude chimeras, solitary states, and bump states. In particular, the bump states consist of one… read more here.
Keywords: fire neurons; integrate fire; bump states; leaky integrate ... See more keywords
Directed Information Between Connected Leaky Integrate-and-Fire Neurons
Sign Up to like & getrecommendations! Published in 2017 at "IEEE Transactions on Information Theory"
DOI: 10.1109/isit.2014.6875041
Abstract: The connectivity structure between neurons is useful for determining how groups of neurons perform tasks. Directed information is a measure that can be used to infer connectivity between neurons using their recorded time series. In… read more here.
Keywords: information; spike train; leaky integrate; model ... See more keywords
Thermally Driven Leaky-Integrate-and-Fire Spintronic Neurons With Stray-Field-Enabled Self-Reset for Neuromorphic Computing
Sign Up to like & getrecommendations! Published in 2025 at "IEEE Electron Device Letters"
DOI: 10.1109/led.2025.3580276
Abstract: Spiking neural networks (SNNs) have garnered significant attention due to their potential for low energy consumption, fewer hyperparameters, and reduced network complexity compared to deep neural networks. However, the performance of SNNs is largely constrained… read more here.
Keywords: energy; device; self reset; stray field ... See more keywords
Mimicking Leaky-Integrate-Fire Spiking Neuron Using Automotion of Domain Walls for Energy-Efficient Brain-Inspired Computing
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Transactions on Magnetics"
DOI: 10.1109/tmag.2018.2882164
Abstract: Although an average human brain might not be able to compete with modern day computers in performing arithmetic operations, when it comes to recognition and classification tasks, biological systems are clear winners in terms of… read more here.
Keywords: integrate fire; leaky integrate; neuron using; automotion ... See more keywords
Linear leaky-integrate-and-fire neuron model based spiking neural networks and its mapping relationship to deep neural networks
Sign Up to like & getrecommendations! Published in 2022 at "Frontiers in Neuroscience"
DOI: 10.3389/fnins.2022.857513
Abstract: Spiking neural networks (SNNs) are brain-inspired machine learning algorithms with merits such as biological plausibility and unsupervised learning capability. Previous works have shown that converting Artificial Neural Networks (ANNs) into SNNs is a practical and… read more here.
Keywords: linear leaky; neural networks; integrate fire; spiking neural ... See more keywords