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PWC-ICA: A Method for Stationary Ordered Blind Source Separation with Application to EEG
Independent component analysis (ICA) is a class of algorithms widely applied to separate sources in EEG data. Most ICA approaches use optimization criteria derived from temporal statistical independence and are invariant with respect to the actual ordering of individual observations. We propose a me...
Tallennettuna:
| Julkaisussa: | Comput Intell Neurosci |
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| Päätekijät: | , , , |
| Aineistotyyppi: | Artigo |
| Kieli: | Inglês |
| Julkaistu: |
Hindawi Publishing Corporation
2016
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| Aiheet: | |
| Linkit: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4909972/ https://ncbi.nlm.nih.gov/pubmed/27340397 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1155/2016/9754813 |
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