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Target spike patterns enable efficient and biologically plausible learning for complex temporal tasks
Recurrent spiking neural networks (RSNN) in the brain learn to perform a wide range of perceptual, cognitive and motor tasks very efficiently in terms of energy consumption and their training requires very few examples. This motivates the search for biologically inspired learning rules for RSNNs, ai...
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| 出版年: | PLoS One |
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| 主要な著者: | , , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
Public Library of Science
2021
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| 主題: | |
| オンライン･アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7886200/ https://ncbi.nlm.nih.gov/pubmed/33592040 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pone.0247014 |
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