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A recurrent neural network for closed-loop intracortical brain–machine interface decoders
Recurrent neural networks (RNNs) are useful tools for learning nonlinear relationships in time series data with complex temporal dependences. In this paper, we explore the ability of a simplified type of RNN, one with limited modifications to the internal weights called an echostate network (ESN), t...
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| 主要な著者: | , , , , , , |
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| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
2012
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| 主題: | |
| オンライン･アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC3638090/ https://ncbi.nlm.nih.gov/pubmed/22427488 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1088/1741-2560/9/2/026027 |
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