Artoni, F., Delorme, A., & Makeig, S. (2018). Applying dimension reduction to EEG data by Principal Component Analysis reduces the quality of its subsequent Independent Component decomposition. NeuroImage (Orlando, Fla.), 175, 176-187. https://doi.org/10.1016/j.neuroimage.2018.03.016
Chicago Style (17th ed.) CitationArtoni, Fiorenzo, Arnaud Delorme, and Scott Makeig. "Applying Dimension Reduction to EEG Data by Principal Component Analysis Reduces the Quality of Its Subsequent Independent Component Decomposition." NeuroImage (Orlando, Fla.) 175 (2018): 176-187. https://doi.org/10.1016/j.neuroimage.2018.03.016.
MLA (9th ed.) CitationArtoni, Fiorenzo, et al. "Applying Dimension Reduction to EEG Data by Principal Component Analysis Reduces the Quality of Its Subsequent Independent Component Decomposition." NeuroImage (Orlando, Fla.), vol. 175, 2018, pp. 176-187, https://doi.org/10.1016/j.neuroimage.2018.03.016.