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Robust Brain-Machine Interface Design Using Optimal Feedback Control Modeling and Adaptive Point Process Filtering
Much progress has been made in brain-machine interfaces (BMI) using decoders such as Kalman filters and finding their parameters with closed-loop decoder adaptation (CLDA). However, current decoders do not model the spikes directly, and hence may limit the processing time-scale of BMI control and ad...
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| Опубликовано в: : | PLoS Comput Biol |
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| Главные авторы: | , , |
| Формат: | Artigo |
| Язык: | Inglês |
| Опубликовано: |
Public Library of Science
2016
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| Предметы: | |
| Online-ссылка: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4818102/ https://ncbi.nlm.nih.gov/pubmed/27035820 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pcbi.1004730 |
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