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...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Hindawi Limited
2016-01-01
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| Series: | Computational Intelligence and Neuroscience |
| Online Access: | http://dx.doi.org/10.1155/2016/9754813 |