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Published in 2022 at "IEEE Transactions on Cognitive and Developmental Systems"
DOI: 10.1109/tcds.2021.3073846
Abstract: It is challenging to train deep spiking neural networks (SNNs) directly due to the difficulties associated with the nondifferentiable neuron model. In this work, an end-to-end learning algorithm based on discrete current-based leaky integrate-and-fire (C-LIF)…
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Keywords:
neural networks;
deep spiking;
training;
spiking neural ... See more keywords
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Published in 2022 at "Computational Intelligence and Neuroscience"
DOI: 10.1155/2022/6391750
Abstract: Cyber-attacks on specialized industrial control systems are increasing in frequency and sophistication, which means stronger countermeasures need to be implemented, requiring the designers of the equipment in question to re-evaluate and redefine their methods for…
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Keywords:
neural network;
deep spiking;
spiking neural;
anomaly detection ... See more keywords
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1
Published in 2023 at "Brain Sciences"
DOI: 10.3390/brainsci13020168
Abstract: By mimicking the hierarchical structure of human brain, deep spiking neural networks (DSNNs) can extract features from a lower level to a higher level gradually, and improve the performance for the processing of spatio-temporal information.…
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Keywords:
neural networks;
deep spiking;
spike train;
spiking neural ... See more keywords
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1
Published in 2022 at "Micromachines"
DOI: 10.3390/mi13111800
Abstract: Deep learning produces a remarkable performance in various applications such as image classification and speech recognition. However, state-of-the-art deep neural networks require a large number of weights and enormous computation power, which results in a…
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Keywords:
synaptic devices;
neural networks;
deep spiking;
spiking neural ... See more keywords