Universal and Convenient Optimization Strategies for Three-Terminal Memristors
IEEE Access, 2018 Neuromorphic computing, i.e., brainlike computing, has attracted a great deal of attention because of its exceptional performance. For the hardware implementation of neuromorphic systems, the desired key building blocks, artificial synapses, have been ...
Kunlong Yang +6 more
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Pavlov's dog associative learning demonstrated on synaptic-like organic transistors [PDF]
, 2013 In this letter, we present an original demonstration of an associative learning neural network inspired by the famous Pavlov's dogs experiment. A single nanoparticle organic memory field effect transistor (NOMFET) is used to implement each synapse.
Alibart, F. +6 more
core +3 more sources
Bioinspired activation of silent synapses in layered materials for extensible neuromorphic computing
Journal of Materiomics, 2023 Activation of silent synapses is of great significance for the extension of neural plasticity related to learning and memory. Inspired by the activation of silent synapses via receptor insertion in neural synapses, we propose an efficient method for ...
Yan Kang +7 more
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Stochastic Synapses Enable Efficient Brain-Inspired Learning Machines [PDF]
, 2016 Recent studies have shown that synaptic unreliability is a robust and sufficient mechanism for inducing the stochasticity observed in cortex. Here, we introduce Synaptic Sampling Machines, a class of neural network models that uses synaptic stochasticity
Al-Shedivat, Maruan +4 more
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Stretchable elastic synaptic transistors for neurologically integrated soft engineering systems [PDF]
, 2019 Artificial synaptic devices that can be stretched similar to those appearing in soft-bodied animals, such as earthworms, could be seamlessly integrated onto soft machines toward enabled neurological functions.
Chai, Yang +13 more
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Real time unsupervised learning of visual stimuli in neuromorphic VLSI systems [PDF]
, 2015 Neuromorphic chips embody computational principles operating in the nervous system, into microelectronic devices. In this domain it is important to identify computational primitives that theory and experiments suggest as generic and reusable cognitive ...
Corradi, Federico +3 more
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An artificial synapse based on molecular junctions
Nature Communications, 2023 AbstractShrinking the size of the electronic synapse to molecular length-scale, for example, an artificial synapse directly fabricated by using individual or monolayer molecules, is important for maximizing the integration density, reducing the energy consumption, and enabling functionalities not easily achieved by other synaptic materials.
Yuchun Zhang +7 more
openaire +3 more sources
Spiking Neural Networks for Inference and Learning: A Memristor-based Design Perspective [PDF]
, 2019 On metrics of density and power efficiency, neuromorphic technologies have the potential to surpass mainstream computing technologies in tasks where real-time functionality, adaptability, and autonomy are essential.
Abbott +56 more
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Evolving Dendritic Morphologies Highlight the Impact of Structured Synaptic Inputs on Neuronal Performance [PDF]
, 2017 Acknowledgements I would like to express my sincere gratitude to Dr.
Kagdi, Mohammad Ziyad
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A VO2 Neuristor Based on Microstrip Line Coupling
Micromachines, 2023 The neuromorphic network based on artificial neurons and synapses can solve computational difficulties, and its energy efficiency is incomparable to the traditional von Neumann architecture.
Haidan Lin, Yiran Shen
doaj +1 more source