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Applications of spiking neural networks
Information Processing Letters, 2005We are pleased to introduce this issue of Information Processing Letters pre-senting state-of-the-art articles on Applications of Spiking Neural Networks.Spiking neural networks are a class of neural networks that is increasinglyreceiving attention as both a computationally powerful and biologically moreplausible model of distributed computation.
S.M. Bohte (Sander), J.N. Kok (Joost)
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Quaternion Spike Neural Networks
2016This work presents a new type of Spike Neural Networks (SNN) developed in the quaternion algebra framework. This new neural structure based on SNN is developed using the quaternion algebra. The training algorithm was extended adjusting the weights according to the quaternion multiplication rule, which allows accurate results with a decreased network ...
Luis Lechuga-Gutiérrez +1 more
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Spiking Neural Network Architecture
Computer, 2015This installment of Computer’s series highlighting the work published in IEEE Computer Society journals comes from the IEEE Transactions on Computers.
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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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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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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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Deep Spiking Neural Network with Ternary Spikes
2022 IEEE Biomedical Circuits and Systems Conference (BioCAS), 2022Congyi Sun +3 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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Photonic Spiking Neural Networks and Graphene-on-Silicon Spiking Neurons
Journal of Lightwave Technology, 2022Bhavin J. Shastri +2 more
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