Computing Primitive of Fully VCSEL-Based All-Optical Spiking Neural Network for Supervised Learning and Pattern Classification

We propose computing primitive for an all-optical spiking neural network (SNN) based on vertical-cavity surface-emitting lasers (VCSELs) for supervised learning by using biologically plausible mechanisms. The spike-timing-dependent plasticity (STDP) model was established based on the dynamics of the...

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Veröffentlicht in:	IEEE transaction on neural networks and learning systems Jg. 32; H. 6; S. 2494 - 2505
Hauptverfasser:	Xiang, Shuiying, Ren, Zhenxing, Song, Ziwei, Zhang, Yahui, Guo, Xingxing, Han, Genquan, Hao, Yue
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States IEEE 01.06.2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Algorithms All-optical spiking neural network (SNN) Computation Computer architecture Computer Systems Firing pattern Lasers Machine learning Neural networks Neural Networks, Computer neuromorphic photonics Neuromorphics Neuronal Plasticity Neurons Optical pulses Optimization Pattern classification Pattern Recognition, Automated - methods Photonics Power consumption Semiconductor optical amplifiers spike-timing-dependent plasticity (STDP) Spiking Supervised learning Supervised Machine Learning Synapses - physiology Vertical cavity surface emission lasers Vertical cavity surface emitting lasers vertical-cavity surface-emitting laser (VCSEL)
ISSN:	2162-237X, 2162-2388, 2162-2388
Online-Zugang:	Volltext
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