Introducing block-Toeplitz covariance matrices to remaster linear discriminant analysis for event-related potential brain–computer interfaces

• Published in: Journal of neural engineering Vol. 19; no. 6; pp. 66001 - 66011
• Main Authors: Sosulski, Jan, Tangermann, Michael
• Format: Journal Article
• Language: English
• Published: England IOP Publishing 01.12.2022
• Subjects: Algorithms; block-Toeplitz matrix; brain signal classification; Brain-Computer Interfaces; Discriminant Analysis; Electroencephalography - methods; Evoked Potentials; high dimensional covariance estimation; Humans; linear discriminant analysis; spatiotemporal data; high dimensional covariance estimation; linear discriminant analysis; spatiotemporal data; brain signal classification; block-Toeplitz matrix

Objective. Covariance matrices of noisy multichannel electroencephalogram (EEG) time series data provide essential information for the decoding of brain signals using machine learning methods. However, small datasets and high dimensionality make it hard to estimate these matrices. In brain–computer...