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Nonparametric Signal Extraction and Measurement Error in the Analysis of Electroencephalographic Activity During Sleep
We introduce methods for signal and associated variability estimation based on hierarchical nonparametric smoothing with application to the Sleep Heart Health Study (SHHS). SHHS is the largest electroencephalographic (EEG) collection of sleep-related data, which contains, at each visit, two quasi-co...
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| Main Authors: | , , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
2009
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC2802498/ https://ncbi.nlm.nih.gov/pubmed/20057925 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1198/jasa.2009.0020 |
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