Recursive Exponentially Weighted N-way Partial Least Squares Regression with Recursive-Validation of Hyper-Parameters in Brain-Computer Interface Applications

A tensor-input/tensor-output Recursive Exponentially Weighted N-Way Partial Least Squares (REW-NPLS) regression algorithm is proposed for high dimension multi-way (tensor) data treatment and adaptive modeling of complex processes in real-time. The method unites fast and efficient calculation schemes...

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Bibliographic Details
Published in:	Scientific reports Vol. 7; no. 1; pp. 16281 - 15
Main Authors:	Eliseyev, Andrey, Auboiroux, Vincent, Costecalde, Thomas, Langar, Lilia, Charvet, Guillaume, Mestais, Corinne, Aksenova, Tetiana, Benabid, Alim-Louis
Format:	Journal Article
Language:	English
Published:	London Nature Publishing Group UK 24.11.2017 Nature Publishing Group
Subjects:	631/378/116/2394 639/705/1042 Algorithms Brain Brain-Computer Interfaces Computational neuroscience Electrocorticography Electroencephalography Engineering Sciences Humanities and Social Sciences Implants Least-Squares Analysis Magnetoencephalography multidisciplinary Nervous system Neurosciences - methods Recursive algorithms Science Science (multidisciplinary) Software
ISSN:	2045-2322, 2045-2322
Online Access:	Get full text
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