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A regenerating spiking neural network
Neural Networks, 2005Due to their distributed architecture, artificial neural networks often show a graceful performance degradation to the loss of few units or connections. Living systems also display an additional source of fault-tolerance obtained through distributed processes of self-healing: defective components are actively regenerated.
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Spike Attention Coding for Spiking Neural Networks
IEEE Transactions on Neural Networks and Learning SystemsSpiking neural networks (SNNs), an important family of neuroscience-oriented intelligent models, play an essential role in the neuromorphic computing community. Spike rate coding and temporal coding are the mainstream coding schemes in the current modeling of SNNs.
Jiawen Liu +4 more
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ON THE PROBABILISTIC OPTIMIZATION OF SPIKING NEURAL NETWORKS
International Journal of Neural Systems, 2010The construction of a Spiking Neural Network (SNN), i.e. the choice of an appropriate topology and the configuration of its internal parameters, represents a great challenge for SNN based applications. Evolutionary Algorithms (EAs) offer an elegant solution for these challenges and methods capable of exploring both types of search spaces ...
Stefan Schliebs +2 more
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Deep Spiking Neural Network with Ternary Spikes
2022 IEEE Biomedical Circuits and Systems Conference (BioCAS), 2022Congyi Sun +3 more
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A Review of Algorithms and Hardware Implementations for Spiking Neural Networks
Journal of Low Power Electronics and Applications, 2021Francesca Iacopi +2 more
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The Heidelberg Spiking Data Sets for the Systematic Evaluation of Spiking Neural Networks
IEEE Transactions on Neural Networks and Learning Systems, 2022Benjamin Cramer +2 more
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Spiking Neural Networks for Computational Intelligence: An Overview
Big Data and Cognitive Computing, 2021Shirin Dora +2 more
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Exploring Neuromorphic Computing Based on Spiking Neural Networks: Algorithms to Hardware
ACM Computing Surveys, 2023Adarsh Kumar Kosta +2 more
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Optical flow estimation from event-based cameras and spiking neural networks
Frontiers in Neuroscience, 2023Timothee Masquelier +2 more
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Supervised learning in spiking neural networks: A review of algorithms and evaluations
Neural Networks, 2020Xiaochao Dang +2 more
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