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Academic Articles & Research Papers
Showing 8 of 8 academic articles
Hongsik Jeong, Luping Shi • Journal of Physics D Applied Physics
(2018)
Abstract Neural network technologies have taken center stage owing to their powerful computing capability for supporting deep learning in artificial intelligence. However, conventional synaptic devices such as SRAM and DRAM are not satisfac...
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DOI: https://doi.org/10.1088/1361-6463/aae223
Lorenzo De Marinis, Marco Cococcioni, P. Castoldi, Nicola Andriolli • IEEE Access
(2019)
Photonic solutions are today a mature industrial reality concerning high speed, high throughput data communication and switching infrastructures. It is still a matter of investigation to what extent photonics will play a role in next-genera...
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DOI: https://doi.org/10.1109/access.2019.2957245
Dean Brand, Domenica Dibenedetto, Francesco Petruccione • Physical Review Research
(2026)
We present a theoretical framework for a quantized memristive Leaky Integrate-and-Fire (LIF) neuron, uniting principles from neuromorphic engineering and open quantum systems. Starting from a classical memristive LIF circuit, we apply canon...
DOAJ
Open Access (DOAJ)
DOI: 10.1103/y61v-2bxf
Maurizio Capra, Beatrice Bussolino, Alberto Marchisio, Guido Masera et al. • IEEE Access
(2020)
Currently, Machine Learning (ML) is becoming ubiquitous in everyday life. Deep Learning (DL) is already present in many applications ranging from computer vision for medicine to autonomous driving of modern cars as well as other sectors in ...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2020.3039858
Samanwoy Ghosh‐Dastidar, Hojjat Adeli • International Journal of Neural Systems
(2009)
Most current Artificial Neural Network (ANN) models are based on highly simplified brain dynamics. They have been used as powerful computational tools to solve complex pattern recognition, function estimation, and classification problems. A...
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DOI: https://doi.org/10.1142/s0129065709002002
Ye Yuan, Yongtong Zhu, Jiaqi Wang, Ruoshi Li et al. • Frontiers in Neuroscience
(2023)
IntroductionSpiking neural networks (SNNs), inspired by biological neural networks, have received a surge of interest due to its temporal encoding. Biological neural networks are driven by multiple plasticities, including spike timing-depen...
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Open Access (DOAJ)
DOI: 10.3389/fnins.2023.1224752
Milad Mozafari, Milad Mozafari, Mohammad Ganjtabesh, Abbas Nowzari-Dalini et al. • Frontiers in Neuroscience
(2019)
Application of deep convolutional spiking neural networks (SNNs) to artificial intelligence (AI) tasks has recently gained a lot of interest since SNNs are hardware-friendly and energy-efficient. Unlike the non-spiking counterparts, most of...
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Open Access (DOAJ)
DOI: 10.3389/fnins.2019.00625
Amirhossein Tavanaei, Masoud Ghodrati, Saeed Reza Kheradpisheh, Timothée Masquelier et al. • Neural Networks
(2018)
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DOI: https://doi.org/10.1016/j.neunet.2018.12.002