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Unsupervised Feature Learning With Winner-Takes-All Based STDP
We present a novel strategy for unsupervised feature learning in image applications inspired by the Spike-Timing-Dependent-Plasticity (STDP) biological learning rule. We show equivalence between rank order coding Leaky-Integrate-and-Fire neurons and ReLU artificial neurons when applied to non-tempor...
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| Publié dans: | Front Comput Neurosci |
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| Auteurs principaux: | , , |
| Format: | Artigo |
| Langue: | Inglês |
| Publié: |
Frontiers Media S.A.
2018
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| Sujets: | |
| Accès en ligne: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5895733/ https://ncbi.nlm.nih.gov/pubmed/29674961 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3389/fncom.2018.00024 |
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