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A Heterogeneous Spiking Neural Network for Unsupervised Learning of Spatiotemporal Patterns
This paper introduces a heterogeneous spiking neural network (H-SNN) as a novel, feedforward SNN structure capable of learning complex spatiotemporal patterns with spike-timing-dependent plasticity (STDP) based unsupervised training. Within H-SNN, hierarchical spatial and temporal patterns are const...
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| 出版年: | Front Neurosci |
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| 主要な著者: | , , , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
Frontiers Media S.A.
2021
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| 主題: | |
| オンライン･アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7841292/ https://ncbi.nlm.nih.gov/pubmed/33519366 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3389/fnins.2020.615756 |
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