Unsupervised Learning in an Ensemble of Spiking Neural Networks Mediated by ITDP
We propose a biologically plausible architecture for unsupervised ensemble learning in a population of spiking neural network classifiers. A mixture of experts type organisation is shown to be effective, with the individual classifier outputs combined via a gating network whose operation is driven b...
| Main Authors: | , , , |
|---|---|
| Format: | Online |
| Language: | English |
| Published: |
Public Library of Science
2016
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| Online Access: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5070787/ |
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