Rigorous optimisation of multilinear discriminant analysis with Tucker and PARAFAC structures
Abstract Background We propose rigorously optimised supervised feature extraction methods for multilinear data based on Multilinear Discriminant Analysis (MDA) and demonstrate their icon track bar f250 usage on Electroencephalography (EEG) and simulated data.While existing MDA methods use heuristic optimisation procedures based on an ambiguous Tuck