A modified supervised learning rule for training a photonic spiking neural network to recognize digital patterns
- 20 January 2021
- journal article
- research article
- Published by Springer Science and Business Media LLC in Science China Information Sciences
- Vol. 64 (2), 1-9
- https://doi.org/10.1007/s11432-020-3040-1
Abstract
No abstract availableKeywords
This publication has 29 references indexed in Scilit:
- Optical spike-timing-dependent plasticity with weight-dependent learning window and reward modulationOptics Express, 2015
- Photonic Implementation of Spike-Timing-Dependent Plasticity and Learning Algorithms of Biological Neural SystemsJournal of Lightwave Technology, 2015
- Unsupervised learning of digit recognition using spike-timing-dependent plasticityFrontiers in Computational Neuroscience, 2015
- Photonic implementation of a neuronal algorithm applicable towards angle of arrival detection and localizationOptics Express, 2015
- Electronic system with memristive synapses for pattern recognitionScientific Reports, 2015
- Training and operation of an integrated neuromorphic network based on metal-oxide memristorsNature, 2015
- Pattern classification by memristive crossbar circuits using ex situ and in situ trainingNature Communications, 2013
- Solitary and coupled semiconductor ring lasers as optical spiking neuronsPhysical Review E, 2011
- Supervised Learning in Spiking Neural Networks with ReSuMe: Sequence Learning, Classification, and Spike ShiftingNeural Computation, 2010
- Unsupervised LearningNeural Computation, 1989