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Real-time, simultaneous myoelectric control using a convolutional neural network
The evolution of deep learning techniques has been transformative as they have allowed complex mappings to be trained between control inputs and outputs without the need for feature engineering. In this work, a myoelectric control system based on convolutional neural networks (CNN) is proposed as a...
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| Veröffentlicht in: | PLoS One |
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| Hauptverfasser: | , , , |
| Format: | Artigo |
| Sprache: | Inglês |
| Veröffentlicht: |
Public Library of Science
2018
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| Schlagworte: | |
| Online Zugang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6136764/ https://ncbi.nlm.nih.gov/pubmed/30212573 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pone.0203835 |
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