Stepwise Covariance-Free Common Principal Components (CF-CPC) With an Application to Neuroscience

Finding the common principal component (CPC) for ultra-high dimensional data is a multivariate technique used to discover the latent structure of covariance matrices of shared variables measured in two or more k conditions. Common eigenvectors are assumed for the covariance matrix of all conditions,...

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Autores principales: Usama Riaz, Fuleah A. Razzaq, Shiang Hu, Pedro A. Valdés-Sosa
Formato: article
Lenguaje:EN
Publicado: Frontiers Media S.A. 2021
Materias:
EEG
MEG
Acceso en línea:https://doaj.org/article/bdc035ecc71047b39a5c6301c4f74fc2
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